PL: Lecture Notes, single file  Wednesday, December 5th
(text file)

Intro to CS4400/CS5400Tuesday, September 11th

Intro to Programming LanguagesTuesday, September 11th

PLAI §1

Intro to RacketTuesday, September 11th

Side-note: “Goto Statement Considered Harmful”Tuesday, September 11th

A review of “Goto Statement Considered Harmful”, by E.W. DIJKSTRA

This paper tries to convince us that the well-known goto statement should be eliminated from our programming languages or, at least (since I don’t think that it will ever be eliminated), that programmers should not use it. It is not clear what should replace it. The paper doesn’t explain to us what would be the use of the if statement without a goto to redirect the flow of execution: Should all our postconditions consist of a single statement, or should we only use the arithmetic if, which doesn’t contain the offensive goto?

And how will one deal with the case in which, having reached the end of an alternative, the program needs to continue the execution somewhere else?

The author is a proponent of the so-called “structured programming” style, in which, if I get it right, gotos are replaced by indentation. Structured programming is a nice academic exercise, which works well for small examples, but I doubt that any real-world program will ever be written in such a style. More than 10 years of industrial experience with Fortran have proved conclusively to everybody concerned that, in the real world, the goto is useful and necessary: its presence might cause some inconveniences in debugging, but it is a de facto standard and we must live with it. It will take more than the academic elucubrations of a purist to remove it from our languages.

Publishing this would waste valuable paper: Should it be published, I am as sure it will go uncited and unnoticed as I am confident that, 30 years from now, the goto will still be alive and well and used as widely as it is today.

Confidential comments to the editor: The author should withdraw the paper and submit it someplace where it will not be peer reviewed. A letter to the editor would be a perfect choice: Nobody will notice it there!

Quick Intro to RacketTuesday, September 11th

Racket syntax: similar to other Sexpr-based languages.

Reminder: the parens can be compared to C/etc function call parens — they always mean that some function is applied. This is the reason why (+ (1) (2)) won’t work: if you use C syntax that is +(1(), 2()) but 1 isn’t a function so 1() is an error.

An important difference between syntax and semantics. A good way to think about this is the difference between the string 42 stored in a file somewhere (two ASCII values), and the number 42 stored in memory (in some representation). You could also continue with the above example: there is nothing wrong with “murder” — it’s just a word, but murder is something you’ll go to jail for. The evaluation function that Racket uses is actually a function that takes a piece of syntax and returns (or executes) its semantics.


define expressions are used for creating new bindings, do not try to use them to change values. For example, you should not try to write something like (define x (+ x 1)) in an attempt to mimic x = x+1. It will not work.


There are two boolean values built in to Racket: #t (true) and #f (false). They can be used in if statements, for example:

(if (< 2 3) 10 20)  -->  10

because (< 2 3) evaluates to #t. As a matter of fact, any value except for #f is considered to be true, so:

(if 0 1 2)        -->  1  ; all of these are "truthy"
(if "false" 1 2)  -->  1
(if "" 1 2)      -->  1
(if null 1 2)    -->  1
(if #t 1 2)      -->  1  ; including the true value
(if #f 1 2)      -->  2  ; the only false value
(if #false 1 2)  -->  2  ; another way to write it
(if false 1 2)    -->  2  ; also false since it's bound to #f

Note: Racket is a functional language — so everything has a value.

This means that the expression

(if test consequent)

has no meaning when test evaluates to #f. This is unlike Pascal/C where statements do something (side effect) like printing or an assignment — here an if statement with no alternate part will just do nothing if the test is false… Racket, however, must return some value — it could decide on simply returning #f (or some unspecified value) as the value of

(if #f something)

as some implementations do, but Racket just declares it a syntax error. (As we will see in the future, Racket has a more convenient when with a clearer intention.)


Well, almost everything is a value…

There are certain things that are part of Racket’s syntax — for example if and define are special forms, they do not have a value! More about this shortly.

(Bottom line: much more things do have a value, compared with other languages.)


cond is used for a ifelse ifelse ifelse … sequence. The problem is that nested ifs are inconvenient. For example,

(define (digit-num n)
  (if (<= n 9)
    1
    (if (<= n 99)
      2
      (if (<= n 999)
        3
        (if (<= n 9999)
          4
          "a lot")))))

In C/Java/Whatever, you’d write:

function digit_num(n) {
  if (n <= 9)        return 1;
  else if (n <= 99)  return 2;
  else if (n <= 999)  return 3;
  else if (n <= 9999) return 4;
  else return "a lot";
}

(Side question: why isn’t there a return statement in Racket?)

But trying to force Racket code to look similar:

(define (digit-num n)
  (if (<= n 9)
    1
  (if (<= n 99)
    2
  (if (<= n 999)
    3
  (if (<= n 9999)
    4
    "a lot")))))

is more than just bad taste — the indentation rules are there for a reason, the main one is that you can see the structure of your program at a quick glance, and this is no longer true in the above code. (Such code will be penalized!)

So, instead of this, we can use Racket’s cond statement, like this:

(define (digit-num n)
  (cond [(<= n 9)    1]
        [(<= n 99)  2]
        [(<= n 999)  3]
        [(<= n 9999) 4]
        [else        "a lot"]))

Note that else is a keyword that is used by the cond form — you should always use an else clause (for similar reasons as an if, to avoid an extra expression evaluation there, and we will need it when we use a typed language). Also note that square brackets are read by DrRacket like round parens, it will only make sure that the paren pairs match. We use this to make code more readable — specifically, there is a major difference between the above use of [] from the conventional use of (). Can you see what it is?

The general structure of a cond:

(cond [test-1 expr-1]
      [test-2 expr-2]
      ...
      [test-n expr-n]
      [else  else-expr])

Example for using an if expression, and a recursive function:

(define (fact n)
  (if (zero? n)
    1
    (* n (fact (- n 1)))))

Use this to show the different tools, especially:

An example of converting it to tail recursive form:

(define (helper n acc)
  (if (zero? n)
    acc
    (helper (- n 1) (* acc n))))

(define (fact n)
  (helper n 1))

Additional notes about homework submissions:

Lists & RecursionTuesday, September 18th

Lists are a fundamental Racket data type.

A list is defined as either:

  1. the empty list (null, empty, or '()),

  2. a pair (cons cell) of anything and a list.

As simple as this may seem, it gives us precise formal rules to prove that something is a list.

Examples:

null
(cons 1 null)
(cons 1 (cons 2 (cons 3 null)))
(list 1 2 3) ; a more convenient function to get the above

List operations — predicates:

null? ; true only for the empty list
pair? ; true for any cons cell
list? ; this can be defined using the above

We can derive list? from the above rules:

(define (list? x)
  (if (null? x)
    #t
    (and (pair? x) (list? (rest x)))))

or better:

(define (list? x)
  (or (null? x)
      (and (pair? x) (list? (rest x)))))

But why can’t we define list? more simply as

(define (list? x)
  (or (null? x) (pair? x)))

The difference between the above definition and the proper one can be observed in the full Racket language, not in the student languages (where there are no pairs with non-list values in their tails).

List operations — destructors for pairs (cons cells):

first
rest

Traditionally called car, cdr.

Also, any c<x>r combination for <x> that is made of up to four as and/or ds — we will probably not use much more than cadr, caddr etc.


Example for recursive function involving lists:

(define (list-length list)
  (if (null? list)
    0
    (+ 1 (list-length (rest list)))))

Use different tools, esp:

How come we could use list as an argument — use the syntax checker

(define (list-length-helper list len)
  (if (null? list)
    len
    (list-length-helper (rest list) (+ len 1))))

(define (list-length list)
  (list-length-helper list 0))

Main idea: lists are a recursive structure, so functions that operate on lists should be recursive functions that follow the recursive definition of lists.

Another example for list function — summing a list of numbers

(define (sum-list l)
  (if (null? l)
    0
    (+ (first l) (sum-list (rest l)))))

Also show how to implement rcons, using this guideline.


More examples:

Define reverse — solve the problem using rcons.

rcons can be generalized into something very useful: append.

Redefine reverse using tail recursion.

Some StyleTuesday, September 18th

When you have some common value that you need to use in several places, it is bad to duplicate it. For example:

(define (how-many a b c)
  (cond [(> (* b b) (* 4 a c)) 2]
        [(= (* b b) (* 4 a c)) 1]
        [(< (* b b) (* 4 a c)) 0]))

What’s bad about it?

In general, the ability to use names is probably the most fundamental concept in computer science — the fact that makes computer programs what they are.

We already have a facility to name values: function arguments. We could split the above function into two like this:

(define (how-many-helper b^2 4ac) ; note: valid names!
  (cond [(> b^2 4ac) 2]
        [(= b^2 4ac) 1]
        [else        0]))

(define (how-many a b c)
  (how-many-helper (* b b) (* 4 a c)))

But instead of the awkward solution of coming up with a new function just for its names, we have a facility to bind local names — let. In general, the syntax for a let special form is

(let ([id expr] ...) expr)

For example,

(let ([x 1] [y 2]) (+ x y))

But note that the bindings are done “in parallel”, for example, try this:

(let ([x 1] [y 2])
  (let ([x y] [y x])
    (list x y)))

(Note that “in parallel” is quoted here because it’s not really parallelism, but just a matter of scopes: the RHSs are all evaluated in the surrounding scope!)

Using this for the above problem:

(define (how-many a b c)
  (let ([b^2 (* b b)]
        [4ac (* 4 a c)])
    (cond [(> b^2 4ac) 2]
          [(= b^2 4ac) 1]
          [else        0])))

Some notes on writing code (also see the style-guide in the handouts section)

Code quality will be graded to in this course!


The fact that in Racket we can use functions as values is very useful — for example, map, foldl & foldr, many more.

Example:

;; every? : (A -> Boolean) (Listof A) -> Boolean
;; Returns false if any element of lst fails
;; the given pred, true if all pass pred.
(define (every? pred lst)
  (or (null? lst)
      (and (pred (first lst))
          (every? pred (rest lst)))))

Tail callsTuesday, September 18th

You should generally know what tail calls are, but here’s a quick review of the subject. A function call is said to be in tail position if there is no context to “remember” when you’re calling it. Very roughly, this means that function calls that are not nested in argument expressions of another call are tail calls. This definition is something that depends on a context, for example, in an expression like

(if (huh?)
  (foo (add1 (* x 3)))
  (foo (/ x 2)))

both calls to foo are tail calls, but they’re tail calls of this expression and therefore apply to this context. It might be that this code is inside another call, as in

(blah (if (huh?)
        (foo (add1 (* x 3)))
        (foo (/ x 2)))
      something-else)

and the foo calls are now not in tail position. The main feature of all Scheme implementations including Racket wrt tail calls is that calls that are in tail position of a function are said to be “eliminated”. That means that if we’re in an f function, and we’re about to call g in tail position and therefore whatever g returns would be the result of f too, then when Racket does the call to g it doesn’t bother keeping the f context — it won’t remember that it needs to “return” to f and will instead return straight to its caller. In other words, when you think about a conventional implementation of function calls as frames on a stack, Racket will get rid of a stack frame when it can.

Another way to see this is to use DrRacket’s stepper to step through a function call. The stepper is generally an alternative debugger, where instead of visualizing stack frames it assembles an expression that represents these frames. Now, in the case of tail calls, there is no room in such a representation to keep the call — and the thing is that in Racket that’s perfectly fine since these calls are not kept on the call stack.

Note that there are several names for this feature:

When should you use tail calls?

Often, people who are aware of tail calls will try to use them always. That’s not always a good idea. You should generally be aware of the tradeoffs when you consider what style to use. The main thing to remember is that tail-call elimination is a property that helps reducing space use (stack space) — often reducing it from linear space to constant space. This can obviously make things faster, but usually the speedup is just a constant factor since you need to do the same number of iterations anyway, so you just reduce the time spent on space allocation.

Here is one such example that we’ve seen:

(define (list-length-1 list)
  (if (null? list)
    0
    (+ 1 (list-length-1 (rest list)))))

;; versus

(define (list-length-helper list len)
  (if (null? list)
    len
    (list-length-helper (rest list) (+ len 1))))
(define (list-length-2 list)
  (list-length-helper list 0))

In this case the first (recursive) version version consumes space linear to the length of the list, whereas the second version needs only constant space. But if you consider only the asymptotic runtime, they are both O(length(l)).

A second example is a simple implementation of map:

(define (map-1 f l)
  (if (null? l) l (cons (f (first l)) (map-1 f (rest l)))))

;; versus

(define (map-helper f l acc)
  (if (null? l)
    (reverse acc)
    (map-helper f (rest l) (cons (f (first l)) acc))))
(define (map-2 f l)
  (map-helper f l '()))

In this case, both the asymptotic space and the runtime consumption are the same. In the recursive case we have a constant factor for the stack space, and in the iterative one (the tail-call version) we also have a similar factor for accumulating the reversed list. In this case, it is probably better to keep the first version since the code is simpler. In fact, Racket’s stack space management can make the first version run faster than the second — so optimizing it into the second version is useless.

Note on TypesTuesday, September 18th

Types can become interesting when dealing with higher-order functions. For example, map receives a function and a list of some type, and applies the function over this list to accumulate its output, so its type is:

;; map : (A -> B) (Listof A) -> (Listof B)

Actually, map can use more than a single list, it will apply the function on the first element in all lists, then the second and so on. So the type of map with two lists can be described as:

;; map : (A B -> C) (Listof A) (Listof B) -> (Listof C)

Here’s a hairy example — what is the type of this function:

(define (foo x y)
  (map map x y))

Begin by what we know — both maps, call them map1 and map2, have the double- and single-list types of map respectively, here they are, with different names for types:

;; the first `map', consumes a function and two lists
map1 : (A B -> C) (Listof A) (Listof B) -> (Listof C)

;; the second `map', consumes a function and one list
map2 : (X -> Y) (Listof X) -> (Listof Y)

Now, we know that map2 is the first argument to map1, so the type of map1s first argument should be the type of map2:

(A B -> C) = (X -> Y) (Listof X) -> (Listof Y)

From here we can conclude that

A = (X -> Y)

B = (Listof X)

C = (Listof Y)

If we use these equations in map1’s type, we get:

map1 : ((X -> Y) (Listof X) -> (Listof Y))
      (Listof (X -> Y))
      (Listof (Listof X))
      -> (Listof (Listof Y))

Now, foo’s two arguments are the 2nd and 3rd arguments of map1, and its result is map1s result, so we can now write the type of foo:

;; foo : (Listof (X -> Y))
;;      (Listof (Listof X))
;;      -> (Listof (Listof Y))
(define (foo x y)
  (map map x y))

This should help you understand why, for example, this will cause a type error:

(foo (list add1 sub1 add1) (list 1 2 3))

and why this is valid:

(foo (list add1 sub1 add1) (map list (list 1 2 3)))

Side-note: Names are importantTuesday, September 18th

An important “discovery” in computer science is that we don’t need names for every intermediate sub-expression — for example, in almost any language we can write the equivalent of:

s = (-b + sqrt(b^2 - 4*a*c)) / (2*a)

instead of

x = b * b
y = 4 * a
y = y * c
x = x - y
x = sqrt(x)
y = -b
x = y + x
y = 2 * a
s = x / y

Such languages are put in contrast to assembly languages, and were all put under the generic label of “high level languages”.

(Here’s an interesting idea — why not do the same for function values?)

BNF, Grammars, the AE LanguageTuesday, September 18th

Getting back to the theme of the course: we want to investigate programming languages, and we want to do that using a programming language.

The first thing when we design a language is to specify the language. For this we use BNF (Backus-Naur Form). For example, here is the definition of a simple arithmetic language:

<AE> ::= <num>
      | <AE> + <AE>
      | <AE> - <AE>

Explain the different parts. Specifically, this is a mixture of low-level (concrete) syntax definition with parsing.

We use this to derive expressions in some language. We start with <AE>, which should be one of these:

<num> is a terminal: when we reach it in the derivation, we’re done. <AE> is a non-terminal: when we reach it, we have to continue with one of the options. It should be clear that the + and the - are things we expect to find in the input — because they are not wrapped in <>s.

We could specify what <num> is (turning it into a <NUM> non-terminal):

<AE> ::= <NUM>
      | <AE> + <AE>
      | <AE> - <AE>

<NUM> ::= 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9
        | <NUM> <NUM>

But we don’t — why? Because in Racket we have numbers as primitives and we want to use Racket to implement our languages. This makes life a lot easier, and we get free stuff like floats, rationals etc.

To use a BNF formally, for example, to prove that 1-2+3 is a valid <AE> expression, we first label the rules:

<AE> ::= <num>        (1)
      | <AE> + <AE>  (2)
      | <AE> - <AE>  (3)

and then we can use them as formal justifications for each derivation step:

<AE>
<AE> + <AE>        ; (2)
<AE> + <num>        ; (1)
<AE> - <AE> + <num> ; (3)
<AE> - <AE> + 3    ; (num)
<num> - <AE> + 3    ; (1)
<num> - <num> + 3  ; (1)
1 - <num> + 3      ; (num)
1 - 2 + 3          ; (num)

This would be one way of doing this. Alternatively, we can can visualize the derivation using a tree, with the rules used at the nodes.

These specifications suffer from being ambiguous: an expression can be derived in multiple ways. Even the little syntax for a number is ambiguous — a number like 123 can be derived in two ways that result in trees that look different. This ambiguity is not a “real” problem now, but it will become one very soon. We want to get rid of this ambiguity, so that there is a single (= deterministic) way to derive all expressions.

There is a standard way to resolve that — we add another non-terminal to the definition, and make it so that each rule can continue to exactly one of its alternatives. For example, this is what we can do with numbers:

<NUM>  ::= <DIGIT> | <DIGIT> <NUM>

<DIGIT> ::= 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9

Similar solutions can be applied to the <AE> BNF — we either restrict the way derivations can happen or we come up with new non-terminals to force a deterministic derivation trees.

As an example of restricting derivations, we look at the current grammar:

<AE> ::= <num>
      | <AE> + <AE>
      | <AE> - <AE>

and instead of allowing an <AE> on both sides of the operation, we force one to be a number:

<AE> ::= <num>
      | <num> + <AE>
      | <num> - <AE>

Now there is a single way to derive any expression, and it is always associating operations to the right: an expression like 1+2+3 can only be derived as 1+(2+3). To change this to left-association, we would use this:

<AE> ::= <num>
      | <AE> + <num>
      | <AE> - <num>

But what if we want to force precedence? Say that our AE syntax has addition and multiplication:

<AE> ::= <num>
      | <AE> + <AE>
      | <AE> * <AE>

We can do that same thing as above and add new non-terminals — say one for “products”:

<AE>  ::= <num>
        | <AE> + <AE>
        | <PROD>

<PROD> ::= <num>
        | <PROD> * <PROD>

Now we must parse any AE expression as additions of multiplications (or numbers). First, note that if <AE> goes to <PROD> and that goes to <num>, then there is no need for an <AE> to go to a <num>, so this is the same syntax:

<AE>  ::= <AE> + <AE>
        | <PROD>

<PROD> ::= <num>
        | <PROD> * <PROD>

Now, if we want to still be able to multiply additions, we can force them to appear in parentheses:

<AE>  ::= <AE> + <AE>
        | <PROD>

<PROD> ::= <num>
        | <PROD> * <PROD>
        | ( <AE> )

Next, note that <AE> is still ambiguous about additions, which can be fixed by forcing the left hand side of an addition to be a factor:

<AE>  ::= <PROD> + <AE>
        | <PROD>

<PROD> ::= <num>
        | <PROD> * <PROD>
        | ( <AE> )

We still have an ambiguity for multiplications, so we do the same thing and add another non-terminal for “atoms”:

<AE>  ::= <PROD> + <AE>
        | <PROD>

<PROD> ::= <ATOM> * <PROD>
        | <ATOM>

<ATOM> ::= <num>
        | ( <AE> )

And you can try to derive several expressions to be convinced that derivation is always deterministic now.

But as you can see, this is exactly the cosmetics that we want to avoid — it will lead us to things that might be interesting, but unrelated to the principles behind programming languages. It will also become much much worse when we have a real language rather such a tiny one.

Is there a good solution? — It is right in our face: do what Racket does — always use fully parenthesized expressions:

<AE> ::= <num>
      | ( <AE> + <AE> )
      | ( <AE> - <AE> )

To prevent confusing Racket code with code in our language(s), we also change the parentheses to curly ones:

<AE> ::= <num>
      | { <AE> + <AE> }
      | { <AE> - <AE> }

But in Racket everything has a value — including those +s and -s, which makes this extremely convenient with future operations that might have either more or less arguments than 2 as well as treating these arithmetic operators as plain functions. In our toy language we will not do this initially (that is, + and - are second order operators: they cannot be used as values). But since we will get to it later, we’ll adopt the Racket solution and use a fully-parenthesized prefix notation:

<AE> ::= <num>
      | { + <AE> <AE> }
      | { - <AE> <AE> }

(Remember that in a sense, Racket code is written in a form of already-parsed syntax…)

Simple ParsingTuesday, September 18th

On to an implementation of a “parser”:

Unrelated to what the syntax actually looks like, we want to parse it as soon as possible — converting the concrete syntax to an abstract syntax tree.

No matter how we write our syntax:

we always mean the same abstract thing — adding the number 3 and the number 4. The essence of this is basically a tree structure with an addition operation as the root and two leaves holding the two numerals.

With the right data definition, we can describe this in Racket as the expression (Add (Num 3) (Num 4)) where Add and Num are constructors of a tree type for syntax, or in a C-like language, it could be something like Add(Num(3),Num(4)).

Similarly, the expression (3-4)+7 will be described in Racket as the expression:

(Add (Sub (Num 3) (Num 4)) (Num 7))

Important note: “expression” was used in two different ways in the above — each way corresponds to a different language, and the result of evaluating the second “expression” is a Racket value that represents the first expression.

To define the data type and the necessary constructors we will use this:

(define-type AE
  [Num Number]
  [Add AE AE]
  [Sub AE AE])

To make things very simple, we will use the above fact through a double-level approach:

This is achieved by the following simple recursive function:

(: parse-sexpr : Sexpr -> AE)
;; parses s-expressions into AEs
(define (parse-sexpr sexpr)
  (cond [(number? sexpr) (Num sexpr)]
        [(and (list? sexpr) (= 3 (length sexpr)))
        (let ([make-node
                (match (first sexpr)
                  ['+ Add]
                  ['- Sub]
                  [else (error 'parse-sexpr "unknown op: ~s"
                              (first sexpr))])
                #| the above is the same as:
                (cond [(equal? '+ (first sexpr)) Add]
                      [(equal? '- (first sexpr)) Sub]
                      [else (error 'parse-sexpr "unknown op: ~s"
                                  (first sexpr))])
                |#])
          (make-node (parse-sexpr (second sexpr))
                      (parse-sexpr (third sexpr))))]
        [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

This function is pretty simple, but as our languages grow, they will become more verbose and more difficult to write. So, instead, we use a new special form: match, which is matching a value and binds new identifiers to different parts (try it with “Check Syntax”). Re-writing the above code using match:

(: parse-sexpr : Sexpr -> AE)
;; parses s-expressions into AEs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n) (Num n)]
    [(list '+ left right)
    (Add (parse-sexpr left) (parse-sexpr right))]
    [(list '- left right)
    (Sub (parse-sexpr left) (parse-sexpr right))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

And finally, to make it more uniform, we will combine this with the function that parses a string into a sexpr so we can use strings to represent our programs:

(: parse : String -> AE)
;; parses a string containing an AE expression to an AE
(define (parse str)
  (parse-sexpr (string->sexpr str)))

The match FormTuesday, September 25th

The syntax for match is

(match value
  [pattern result-expr]
  ...)

The value is matched against each pattern, possibly binding names in the process, and if a pattern matches it evaluates the result expression. The simplest form of a pattern is simply an identifier — it always matches and binds that identifier to the value:

(match (list 1 2 3)
  [x x]) ; evaluates to the list

Another simple pattern is a quoted symbol, which matches that symbol. For example:

(match foo
  ['x "yes"]
  [else "no"])

will evaluate to "yes" if foo is the symbol x, and to "no" otherwise. Note that else is not a keyword here — it happens to be a pattern that always succeeds, so it behaves like an else clause except that it binds else to the unmatched-so-far value.

Many patterns look like function application — but don’t confuse them with applications. A (list x y z) pattern matches a list of exactly three items and binds the three identifiers; or if the “arguments” are themselves patterns, match will descend into the values and match them too. More specifically, this means that patterns can be nested:

(match (list 1 2 3)
  [(list x y z) (+ x y z)]) ; evaluates to 6
(match '((1) (2) 3)
  [(list (list x) (list y) z) (+ x y z)]) ; also 6

There is also a cons pattern that matches a non-empty list and then matches the first part against the head for the list and the second part against the tail of the list.

In a list pattern, you can use ... to specify that the previous pattern is repeated zero or more times, and bound names get bound to the list of respective matching. One simple consequent is that the (list hd tl ...) pattern is exactly the same as (cons hd tl), but being able to repeat an arbitrary pattern is very useful:

> (match '((1 2) (3 4) (5 6) (7 8))
    [(list (list x y) ...) (list x y)])
'((1 3 5 7) (2 4 6 8))

A few more useful patterns:

id              -- matches anything, binds `id' to it
_              -- matches anything, but does not bind
(number: n)    -- matches any number and binds it to `n'
(symbol: s)    -- same for symbols
(string: s)    -- strings
(sexpr: s)      -- S-expressions (needed sometimes for Typed Racket)
(and pat1 pat2) -- matches both patterns
(or pat1 pat2)  -- matches either pattern (careful with bindings)

Note that the foo: patterns are all specific to our #lang pl, they are not part of #lang racket or #lang typed/racket

The patterns are tried one by one in-order, and if no pattern matches the value, an error is raised.

Note that ... in a list pattern can follow any pattern, including all of the above, and including nested list patterns.

Here are a few examples — you can try them out with #lang pl untyped at the top of the definitions window. This:

(match x
  [(list (symbol: syms) ...) syms])

matches x against a pattern that accepts only a list of symbols, and binds syms to those symbols. And here’s an example that matches a list of any number of lists, where each of the sub-lists begins with a symbol and then has any number of numbers. Note how the n and s bindings get values for a list of all symbols and a list of lists of the numbers:

> (define (foo x)
    (match x
      [(list (list (symbol: s) (number: n) ...) ...)
      (list 'symbols: s 'numbers: n)]))
> (foo (list (list 'x 1 2 3) (list 'y 4 5)))
'(symbols: (x y) numbers: ((1 2 3) (4 5)))

Here is a quick example for how or is used with two literal alternatives, how and is used to name a specific piece of data, and how or is used with a binding:

> (define (foo x)
    (match x
      [(list (or 1 2 3)) 'single]
      [(list (and x (list 1 _)) 2) x]
      [(or (list 1 x) (list 2 x)) x]))
> (foo (list 3))
'single
> (foo (list (list 1 99) 2))
'(1 99)
> (foo (list 1 10))
10
> (foo (list 2 10))
10

Semantics (= Evaluation)Tuesday, September 25th

PLAI §2

Back to BNF — now, meaning.

An important feature of these BNF specifications: we can use the derivations to specify meaning (and meaning in our context is “running” a program (or “interpreting”, “compiling”, but we will use “evaluating”)). For example:

<AE> ::= <num>        ; <AE> evaluates to the number
      | <AE1> + <AE2> ; <AE> evaluates to the sum of evaluating
                      ;      <AE1> and <AE2>
      | <AE1> - <AE2> ; ... the subtraction of <AE2> from <AE1>
                              (... roughly!)

To do this a little more formally:

a. eval(<num>) = <num> ;*** special rule: translate syntax to value
b. eval(<AE1> + <AE2>) = eval(<AE1>) + eval(<AE2>)
c. eval(<AE1> - <AE2>) = eval(<AE1>) - eval(<AE2>)

Note the completely different roles of the two +s and -s. In fact, it might have been more correct to write:

a. eval("<num>") = <num>
b. eval("<AE1> + <AE2>") = eval("<AE1>") + eval("<AE2>")
c. eval("<AE1> - <AE2>") = eval("<AE1>") - eval("<AE2>")

or even using a marker to denote meta-holes in these strings:

a. eval("$<num>") = <num>
b. eval("$<AE1> + $<AE2>") = eval("$<AE1>") + eval("$<AE2>")
c. eval("$<AE1> - $<AE2>") = eval("$<AE1>") - eval("$<AE2>")

but we will avoid pretending that we’re doing that kind of string manipulation. (For example, it will require specifying what does it mean to return <num> for $<num> (involves string->number), and the fragments on the right side mean that we need to specify these as substring operations.)

Note that there’s a similar kind of informality in our BNF specifications, where we assume that <foo> refers to some terminal or non-terminal. In texts that require more formal specifications (for example, in RFC specifications), each literal part of the BNF is usually double-quoted, so we’d get

<AE> ::= <num> | <AE1> "+" <AE2> | <AE1> "-" <AE2>

An alternative popular notation for eval(X) is [[X]]:

a. [[<num>]] = <num>
b. [[<AE1> + <AE2>]] = [[<AE1>]] + [[<AE2>]]
c. [[<AE1> - <AE2>]] = [[<AE1>]] - [[<AE2>]]

Is there a problem with this definition? Ambiguity:

eval(1 - 2 + 3) = ?

Depending on the way the expression is parsed, we can get either a result of 2 or -4:

eval(1 - 2 + 3) = eval(1 - 2) + eval(3)          [b]
                = eval(1) - eval(2) + eval(3)    [c]
                = 1 - 2 + 3                      [a,a,a]
                = 2

eval(1 - 2 + 3) = eval(1) - eval(2 + 3)          [c]
                = eval(1) - (eval(2) + eval(3))  [a]
                = 1 - (2 + 3)                    [a,a,a]
                = -4

Again, be very aware of confusing subtleties which are extremely important: We need parens around a sub-expression only in one side, why? — When we write:

eval(1 - 2 + 3) = ... = 1 - 2 + 3

we have two expressions, but one stands for an input syntax, and one stands for a real mathematical expression.

In a case of a computer implementation, the syntax on the left is (as always) an AE syntax, and the real expression on the right is an expression in whatever language we use to implement our AE language.

Like we said earlier, ambiguity is not a real problem until the actual parse tree matters. With eval it definitely matters, so we must not make it possible to derive any syntax in multiple ways or our evaluation will be non-deterministic.


Quick exercise:

We can define a meaning for <digit>s and then <num>s in a similar way:

<NUM> ::= <digit> | <digit> <NUM>

eval(0) = 0
eval(1) = 1
eval(2) = 2
...
eval(9) = 9

eval(<digit>) = <digit>
eval(<digit> <NUM>) = 10*eval(<digit>) + eval(<NUM>)

Is this exactly what we want? — Depends on what we actually want…

Side-note: CompositionalityTuesday, September 25th

The example of

<NUM> ::= <digit> | <NUM> <digit>

being a language that is easier to write an evaluator for leads us to an important concept — compositionality. This definition is easier to write an evaluator for, since the resulting language is compositional: the meaning of an expression — for example 123 — is composed out of the meaning of its two parts, which in this BNF are 12 and 3. Specifically, the evaluation of <NUM> <digit> is 10 * the evaluation of the first, plus the evaluation of the second. In the <digit> <NUM> case this is more difficult — the meaning of such a number depends not only on the meaning of the two parts, but also on the <NUM> syntax:

eval(<digit> <NUM>) =
  eval(<digit>) * 10^length(<NUM>) + eval(<NUM>)

This this case this can be tolerable, since the meaning of the expression is still made out of its parts — but imperative programming (when you use side effects) is much more problematic since it is not compositional (at least not in the obvious sense). This is compared to functional programming, where the meaning of an expression is a combination of the meanings of its subexpressions. For example, every sub-expression in a functional program has some known meaning, and these all make up the meaning of the expression that contains them — but in an imperative program we can have a part of the code be x++ — and that doesn’t have a meaning by itself, at least not one that contributes to the meaning of the whole program in a direct way.

(Actually, we can have a well-defined meaning for such an expression: the meaning is going from a world where x is a container of some value N, to a world where the same container has a different value N+1. You can probably see now how this can make things more complicated. On an intuitive level — if we look at a random part of a functional program we can tell its meaning, so building up the meaning of the whole code is easy, but in an imperative program, the meaning of a random part is pretty much useless.)

Implementing an EvaluatorTuesday, September 25th

Now continue to implement the semantics of our syntax — we express that through an eval function that evaluates an expression.

We use a basic programming principle — splitting the code into two layers, one for parsing the input, and one for doing the evaluation. Doing this avoids the mess we’d get into otherwise, for example:

(define (eval sexpr)
  (match sexpr
    [(number: n) n]
    [(list '+ left right) (+ (eval left) (eval right))]
    [(list '- left right) (- (eval left) (eval right))]
    [else (error 'eval "bad syntax in ~s" sexpr)]))

This is messy because it combines two very different things — syntax and semantics — into a single lump of code. For this particular kind of evaluator it looks simple enough, but this is only because it’s simple enough that all we do is replace constructors by arithmetic operations. Later on things will get more complex, and bundling the evaluator with the parser will be more problematic. (Note: the fact that we can replace constructors with the run-time operators mean that we have a very simple, calculator-like language, and that we can, in fact, “compile” all programs down to a number.)

If we split the code, we can easily include decisions like making

{+ 1 {- 3 "a"}}

syntactically invalid. (Which is not, BTW, what Racket does…) (Also, this is like the distinction between XML syntax and well-formed XML syntax.)

An additional advantage is that by using two separate components, it is simple to replace each one, making it possible to change the input syntax, and the semantics independently — we only need to keep the same interface data (the AST) and things will work fine.

Our parse function converts an input syntax to an abstract syntax tree (AST). It is abstract exactly because it is independent of any actual concrete syntax that you type in, print out etc.

Implementing The AE LanguageTuesday, September 25th

Back to our eval — this will be its (obvious) type:

(: eval : AE -> Number)
;; consumes an AE and computes
;; the corresponding number

which leads to some obvious test cases:

(equal? 3 (eval (parse "3")))
(equal? 7 (eval (parse "{+ 3 4}")))
(equal? 6 (eval (parse "{+ {- 3 4} 7}")))

which from now on we will write using the new test form that the #lang pl language provides:

(test (eval (parse "3"))            => 3)
(test (eval (parse "{+ 3 4}"))      => 7)
(test (eval (parse "{+ {- 3 4} 7}")) => 6)

Note that we’re testing only at the interface level — only running whole functions. For example, you could think about a test like:

(test (parse "{+ {- 3 4} 7}")
      => (Add (Sub (Num 3) (Num 4)) (Num 7)))

but the details of parsing and of the constructor names are things that nobody outside of our evaluator cares about — so we’re not testing them. In fact, we shouldn’t even mention parse in these tests, since it is not part of the public interface of our users; they only care about using it as a compiler-like black box. (This is sometimes called “integration tests”.) We’ll address this shortly.

Like everything else, the structure of the recursive eval code follows the recursive structure of its input. In HtDP terms, our template is:

(: eval : AE -> Number)
(define (eval expr)
  (cases expr
    [(Num n)  ... n ...]
    [(Add l r) ... (eval l) ... (eval r) ...]
    [(Sub l r) ... (eval l) ... (eval r) ...]))

In this case, filling in the gaps is very simple

(: eval : AE -> Number)
(define (eval expr)
  (cases expr
    [(Num n)  n]
    [(Add l r) (+ (eval l) (eval r))]
    [(Sub l r) (- (eval l) (eval r))]))

We now further combine eval and parse into a single run function that evaluates an AE string.

(: run : String -> Number)
;; evaluate an AE program contained in a string
(define (run str)
  (eval (parse str)))

This function becomes the single public entry point into our code, and the only thing that should be used in tests that verify our interface:

(test (run "3")            => 3)
(test (run "{+ 3 4}")      => 7)
(test (run "{+ {- 3 4} 7}") => 6)

The resulting full code is:

#lang pl

#| BNF for the AE language:
  <AE> ::= <num>
          | { + <AE> <AE> }
          | { - <AE> <AE> }
          | { * <AE> <AE> }
          | { / <AE> <AE> }
|#

;; AE abstract syntax trees
(define-type AE
  [Num Number]
  [Add AE AE]
  [Sub AE AE]
  [Mul AE AE]
  [Div AE AE])

(: parse-sexpr : Sexpr -> AE)
;; parses s-expressions into AEs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n) (Num n)]
    [(list '+ lhs rhs) (Add (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '- lhs rhs) (Sub (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '* lhs rhs) (Mul (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '/ lhs rhs) (Div (parse-sexpr lhs) (parse-sexpr rhs))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

(: parse : String -> AE)
;; parses a string containing an AE expression to an AE AST
(define (parse str)
  (parse-sexpr (string->sexpr str)))

(: eval : AE -> Number)
;; consumes an AE and computes the corresponding number
(define (eval expr)
  (cases expr
    [(Num n)  n]
    [(Add l r) (+ (eval l) (eval r))]
    [(Sub l r) (- (eval l) (eval r))]
    [(Mul l r) (* (eval l) (eval r))]
    [(Div l r) (/ (eval l) (eval r))]))

(: run : String -> Number)
;; evaluate an AE program contained in a string
(define (run str)
  (eval (parse str)))

;; tests
(test (run "3") => 3)
(test (run "{+ 3 4}") => 7)
(test (run "{+ {- 3 4} 7}") => 6)

(Note that the tests are done with a test form, which we mentioned above.)

For anyone who thinks that Racket is a bad choice, this is a good point to think how much code would be needed in some other language to do the same as above.

Intro to Typed RacketTuesday, September 25th

The plan:

Types

Typed Racket will be both similar to and very different from anything you’ve seen before.

Why types?

–> They will help you. A lot.

Structuring programs

Why Typed Racket?

Racket is the language we all know, and it has the benefits that we discussed earlier. Mainly, it is an excellent language for experimenting with programming languages.

[Also: the development of Typed Racket is happening here in Northeastern, and will benefit from your feedback.]

How is Typed Racket different from Racket

Examples

(: digit-num : Number -> (U Number String))
(define (digit-num n)
  (cond [(<= n 9)    1]
        [(<= n 99)  2]
        [(<= n 999)  3]
        [(<= n 9999) 4]
        [else        "a lot"]))

(: fact : Number -> Number)
(define (fact n)
  (if (zero? n)
    1
    (* n (fact (- n 1)))))

(: helper : Number Number -> Number)
(define (helper n acc)
  (if (zero? n)
    acc
    (helper (- n 1) (* acc n))))
(: fact : Number -> Number)
(define (fact n)
  (helper n 1))

(: fact : Number -> Number)
(define (fact n)
  (: helper : Number Number -> Number)
  (define (helper n acc)
    (if (zero? n)
      acc
      (helper (- n 1) (* acc n))))
  (helper n 1))

(: every? : (All (A) (A -> Boolean) (Listof A) -> Boolean))
;; Returns false if any element of lst fails the given pred,
;; true if all pass pred.
(define (every? pred lst)
  (or (null? lst)
      (and (pred (first lst))
          (every? pred (rest lst)))))

(define-type AE
  [Num Number]
  [Add AE AE]
  [Sub AE AE])

;; the only difference in the following definition is
;; using (: <name> : <type>) instead of ";; <name> : <type>"

(: parse-sexpr : Sexpr -> AE)
;; parses s-expressions into AEs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n) (Num n)]
    [(list '+ left right)
    (Add (parse-sexpr left) (parse-sexpr right))]
    [(list '- left right)
    (Sub (parse-sexpr left) (parse-sexpr right))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

More interesting examples

Bindings & SubstitutionTuesday, September 25th

We now get to an important concept: substitution.

Even in our simple language, we encounter repeated expressions. For example, if we want to compute the square of some expression:

{* {+ 4 2} {+ 4 2}}

Why would we want to get rid of the repeated sub-expression?

So, the normal way to avoid redundancy is to introduce an identifier. Even when we speak, we might say: “let x be 4 plus 2, multiply x by x”.

(These are often called “variables”, but we will try to avoid this name: what if the identifier does not change (vary)?)

To get this, we introduce a new form into our language:

{with {x {+ 4 2}}
  {* x x}}

We expect to be able to reduce this to:

{* 6 6}

by substituting 6 for x in the body sub-expression of with.

A little more complicated example:

{with {x {+ 4 2}}
  {with {y {* x x}}
    {+ y y}}}
[add]  = {with {x 6} {with {y {* x x}} {+ y y}}}
[subst]= {with {y {* 6 6}} {+ y y}}
[mul]  = {with {y 36} {+ y y}}
[subst]= {+ 36 36}
[add]  = 72

WAE: Adding Bindings to AETuesday, September 25th

PLAI §3

To add this to our language, we start with the BNF. We now call our language “WAE” (With+AE):

<WAE> ::= <num>
        | { + <WAE> <WAE> }
        | { - <WAE> <WAE> }
        | { * <WAE> <WAE> }
        | { / <WAE> <WAE> }
        | { with { <id> <WAE> } <WAE> }
        | <id>

Note that we had to introduce two new rules: one for introducing an identifier, and one for using it. This is common in many language specifications, for example define-type introduces a new type, and it comes with cases that allows us to destruct its instances.

For <id> we need to use some form of identifiers, the natural choice in Racket is to use symbols. We can therefore write the corresponding type definition:

(define-type WAE
  [Num  Number]
  [Add  WAE WAE]
  [Sub  WAE WAE]
  [Mul  WAE WAE]
  [Div  WAE WAE]
  [Id  Symbol]
  [With Symbol WAE WAE])

The parser is easily extended to produce these syntax objects:

(: parse-sexpr : Sexpr -> WAE)
;; parses s-expressions into WAEs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(list 'with (list (symbol: name) named) body)
    (With name (parse-sexpr named) (parse-sexpr body))]
    [(list '+ lhs rhs) (Add (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '- lhs rhs) (Sub (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '* lhs rhs) (Mul (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '/ lhs rhs) (Div (parse-sexpr lhs) (parse-sexpr rhs))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

But note that this parser is inconvenient — if any of these expressions:

{* 1 2 3}
{foo 5 6}
{with x 5 {* x 8}}
{with {5 x} {* x 8}}

would result in a “bad syntax” error, which is not very helpful. To make things better, we can add another case for with expressions that are malformed, and give a more specific message in that case:

(: parse-sexpr : Sexpr -> WAE)
;; parses s-expressions into WAEs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(list 'with (list (symbol: name) named) body)
    (With name (parse-sexpr named) (parse-sexpr body))]
    [(cons 'with more)
    (error 'parse-sexpr "bad `with' syntax in ~s" sexpr)]
    [(list '+ lhs rhs) (Add (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '- lhs rhs) (Sub (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '* lhs rhs) (Mul (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '/ lhs rhs) (Div (parse-sexpr lhs) (parse-sexpr rhs))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

and finally, to group all of the parsing code that deals with with expressions (both valid and invalid ones), we can use a single case for both of them:

(: parse-sexpr : Sexpr -> WAE)
;; parses s-expressions into WAEs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(cons 'with more)
    ;; go in here for all sexpr that begin with a 'with
    (match sexpr
      [(list 'with (list (symbol: name) named) body)
        (With name (parse-sexpr named) (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `with' syntax in ~s" sexpr)])]
    [(list '+ lhs rhs) (Add (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '- lhs rhs) (Sub (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '* lhs rhs) (Mul (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '/ lhs rhs) (Div (parse-sexpr lhs) (parse-sexpr rhs))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

And now we’re done with the syntactic part of the with extension.

Quick note — why would we indent With like a normal function in code like this

(With 'x
      (Num 2)
      (Add (Id 'x) (Num 4)))

instead of an indentation that looks like a let

(With 'x (Num 2)
  (Add (Id 'x) (Num 4)))

?

The reason for this is that the second indentation looks like a binding construct (eg, the indentation used in a let expression), but With is not a binding form — it’s a plain function because it’s at the Racket level. You should therefore keep in mind the huge difference between that With and the with that appears in WAE programs:

{with {x 2}
  {+ x 4}}

Another way to look at it: imagine that we intend for the language to be used by Spanish/Chinese/German speakers. In this case we would translate “with”:

{con {x 2} {+ x 4}}
{he  {x 2} {+ x 4}}
{mit {x 2} {+ x 4}}

but we will not do the same for With if we (the language implementors) are English speakers.

Evaluation of withTuesday, September 25th

Now, to make this work, we will need to do some substitutions.

We basically want to say that to evaluate:

{with {id WAE1} WAE2}

we need to evaluate WAE2 with id substituted by WAE1. Formally:

eval( {with {id WAE1} WAE2} )
  = eval( subst(WAE2,id,WAE1) )

There is a more common syntax for substitution (quick: what do I mean by this use of “syntax”?):

eval( {with {id WAE1} WAE2} )
  = eval( WAE2[WAE1/id] )

Side-note: this syntax originates with logicians who used [x/v]e, and later there was a convention that mimicked the more natural order of arguments to a function with e[x->v], and eventually both of these got combined into e[v/x] which is a little confusing in that the left-to-right order of the arguments is not the same as for the subst function.

Now all we need is an exact definition of substitution.

Note that substitution is not the same as evaluation, it’s only a part of the evaluation process. In the previous examples, when we evaluated the expression we did substitutions as well as the usual arithmetic operations that were already part of the AE evaluator. In this last definition there is still a missing evaluation step, see if you can find it.

So let us try to define substitution now:

Substitution (take 1): e[v/i]
To substitute an identifier i in an expression e with an expression v, replace all identifiers in e that have the same name i by the expression v.

This seems to work with simple expressions, for example:

{with {x 5} {+ x x}}  -->  {+ 5 5}
{with {x 5} {+ 10 4}}  -->  {+ 10 4}

however, we crash with an invalid syntax if we try:

{with {x 5} {+ x {with {x 3} 10}}}
  -->  {+ 5 {with {5 3} 10}} ???

— we got to an invalid expression.

To fix this, we need to distinguish normal occurrences of identifiers, and ones that are used as new bindings. We need a few new terms for this:

  1. Binding Instance: a binding instance of an identifier is one that is used to name it in a new binding. In our <WAE> syntax, binding instances are only the <id> position of the with form.

  2. Scope: the scope of a binding instance is the region of program text in which instances of the identifier refer to the value bound in the binding instance. (Note that this definition actually relies on a definition of substitution, because that is what is used to specify how identifiers refer to values.)

  3. Bound Instance (or Bound Occurrence): an instance of an identifier is bound if it is contained within the scope of a binding instance of its name.

  4. Free Instance (or Free Occurrence): An identifier that is not contained in any binding instance of its name is said to be free.

Using this we can say that the problem with the previous definition of substitution is that it failed to distinguish between bound instances (which should be substituted) and binding instances (which should not). So we try to fix this:

Substitution (take 2): e[v/i]
To substitute an identifier i in an expression e with an expression v, replace all instances of i that are not themselves binding instances with the expression v.

First of all, check the previous examples:

{with {x 5} {+ x x}}  -->  {+ 5 5}
{with {x 5} {+ 10 4}}  -->  {+ 10 4}

still work, and

{with {x 5} {+ x {with {x 3} 10}}}
  -->  {+ 5 {with {x 3} 10}}
  -->  {+ 5 10}

also works. However, if we try this:

{with {x 5}
  {+ x {with {x 3}
        x}}}

we get:

-->  {+ 5 {with {x 3} 5}}
-->  {+ 5 5}
-->  10

but we want that to be 8: the inner x should be bound by the closest with that binds it.

The problem is that the new definition of substitution that we have respects binding instances, but it fails to deal with their scope. In the above example, we want the inner with to shadow the outer with’s binding for x.

Substitution (take 3): e[v/i]
To substitute an identifier i in an expression e with an expression v, replace all instances of i that are not themselves binding instances, and that are not in any nested scope, with the expression v.

This avoids bad substitution above, but it is now doing things too carefully:

{with {x 5} {+ x {with {y 3} x}}}

becomes

-->  {+ 5 {with {y 3} x}}
-->  {+ 5 x}

which is an error because x is unbound (and there is reasonable no rule that we can specify to evaluate it).

The problem is that our substitution halts at every new scope, in this case, it stopped at the new y scope, but it shouldn’t have because it uses a different name. In fact, that last definition of substitution cannot handle any nested scope.

Revise again:

Substitution (take 4): e[v/i]
To substitute an identifier i in an expression e with an expression v, replace all instances of i that are not themselves binding instances, and that are not in any nested scope of i, with the expression v.

which, finally, is a good definition. This is just a little too mechanical. Notice that we actually refer to all instances of i that are not in a scope of a binding instance of i, which simply means all free occurrences of i — free in e (why? — remember the definition of “free”?):

Substitution (take 4b): e[v/i]
To substitute an identifier i in an expression e with an expression v, replace all instances of i that are free in e with the expression v.

Based on this we can finally write the code for it:

(: subst : WAE Symbol WAE -> WAE)
;; substitutes the second argument with the third argument in the
;; first argument, as per the rules of substitution; the resulting
;; expression contains no free instances of the second argument
(define (subst expr from to) ; returns expr[to/from]
  (cases expr
    [(Num n) expr]
    [(Add l r) (Add (subst l from to) (subst r from to))]
    [(Sub l r) (Sub (subst l from to) (subst r from to))]
    [(Mul l r) (Mul (subst l from to) (subst r from to))]
    [(Div l r) (Div (subst l from to) (subst r from to))]
    [(Id name) (if (eq? name from) to expr)]
    [(With bound-id named-expr bound-body)
    (if (eq? bound-id from)
      expr          ;*** don't go in!
      (With bound-id
            named-expr
            (subst bound-body from to)))]))

… and this is just the same as writing a formal “paper version” of the substitution rule.

We still have bugs: but we’ll need some more work to get to them.


Before we find the bugs, we need to see when and how substitution is used in the evaluation process.

To modify our evaluator, we will need rules to deal with the new syntax pieces — with expressions and identifiers.

When we see an expression that looks like:

{with {x E1} E2}

we continue by evaluating E1 to get a value V1, we then substitute the identifier x with the expression V1 in E2, and continue by evaluating this new expression. In other words, we have the following evaluation rule:

eval( {with {x E1} E2} )
  = eval( E2[eval(E1)/x] )

So we know what to do with with expressions. How about identifiers? The main feature of subst, as said in the purpose statement, is that it leaves no free instances of the substituted variable around. This means that if the initial expression is valid (did not contain any free variables), then when we go from

{with {x E1} E2}

to

E2[E1/x]

the result is an expression that has no free instances of x. So we don’t need to handle identifiers in the evaluator — substitutions make them all go away.

We can now extend the formal definition of AE to that of WAE:

eval(...) = ... same as the AE rules ...
eval({with {x E1} E2}) = eval(E2[eval(E1)/x])
eval(id) = error!

If you’re paying close attention, you might catch a potential problem in this definition: we’re substituting eval(E1) for x in E2 — an operation that requires a WAE expression, but eval(E1) is a number. (Look at the type of the eval definition we had for AE, then look at the above definition of subst.) This seems like being overly pedantic, but we it will require some resolution when we get to the code. The above rules are easily coded as follows:

(: eval : WAE -> Number)
;; evaluates WAE expressions by reducing them to numbers
(define (eval expr)
  (cases expr
    [(Num n) n]
    [(Add l r) (+ (eval l) (eval r))]
    [(Sub l r) (- (eval l) (eval r))]
    [(Mul l r) (* (eval l) (eval r))]
    [(Div l r) (/ (eval l) (eval r))]
    [(With bound-id named-expr bound-body)
    (eval (subst bound-body
                  bound-id
                  (Num (eval named-expr))))] ;***
    [(Id name) (error 'eval "free identifier: ~s" name)]))

Note the Num expression in the marked line: evaluating the named expression gives us back a number — we need to convert this number into a syntax to be able to use it with subst. The solution is to use Num to convert the resulting number into a numeral (the syntax of a number). It’s not an elegant solution, but it will do for now.

Finally, here are a few test cases. We use a new test special form which is part of the course plugin. The way to use test is with two expressions and an => arrow — DrRacket evaluates both, and nothing will happen if the results are equal. If the results are different, you will get a warning line, but evaluation will continue so you can try additional tests. You can also use an =error> arrow to test an error message — use it with some text from the expected error, ? stands for any single character, and * is a sequence of zero or more characters. (When you use test in your homework, the handin server will abort when tests fail.) We expect these tests to succeed (make sure that you understand why they should succeed).

;; tests
(test (run "5") => 5)
(test (run "{+ 5 5}") => 10)
(test (run "{with {x {+ 5 5}} {+ x x}}") => 20)
(test (run "{with {x 5} {+ x x}}") => 10)
(test (run "{with {x {+ 5 5}} {with {y {- x 3}} {+ y y}}}") => 14)
(test (run "{with {x 5} {with {y {- x 3}} {+ y y}}}") => 4)
(test (run "{with {x 5} {+ x {with {x 3} 10}}}") => 15)
(test (run "{with {x 5} {+ x {with {x 3} x}}}") => 8)
(test (run "{with {x 5} {+ x {with {y 3} x}}}") => 10)
(test (run "{with {x 5} {with {y x} y}}") => 5)
(test (run "{with {x 5} {with {x x} x}}") => 5)
(test (run "{with {x 1} y}") =error> "free identifier")

Putting this all together, we get the following code; trying to run this code will raise an unexpected error…

#lang pl

#| BNF for the WAE language:
    <WAE> ::= <num>
            | { + <WAE> <WAE> }
            | { - <WAE> <WAE> }
            | { * <WAE> <WAE> }
            | { / <WAE> <WAE> }
            | { with { <id> <WAE> } <WAE> }
            | <id>
|#

;; WAE abstract syntax trees
(define-type WAE
  [Num  Number]
  [Add  WAE WAE]
  [Sub  WAE WAE]
  [Mul  WAE WAE]
  [Div  WAE WAE]
  [Id  Symbol]
  [With Symbol WAE WAE])

(: parse-sexpr : Sexpr -> WAE)
;; parses s-expressions into WAEs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(cons 'with more)
    (match sexpr
      [(list 'with (list (symbol: name) named) body)
        (With name (parse-sexpr named) (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `with' syntax in ~s" sexpr)])]
    [(list '+ lhs rhs) (Add (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '- lhs rhs) (Sub (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '* lhs rhs) (Mul (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '/ lhs rhs) (Div (parse-sexpr lhs) (parse-sexpr rhs))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

(: parse : String -> WAE)
;; parses a string containing a WAE expression to a WAE AST
(define (parse str)
  (parse-sexpr (string->sexpr str)))

(: subst : WAE Symbol WAE -> WAE)
;; substitutes the second argument with the third argument in the
;; first argument, as per the rules of substitution; the resulting
;; expression contains no free instances of the second argument
(define (subst expr from to)
  (cases expr
    [(Num n) expr]
    [(Add l r) (Add (subst l from to) (subst r from to))]
    [(Sub l r) (Sub (subst l from to) (subst r from to))]
    [(Mul l r) (Mul (subst l from to) (subst r from to))]
    [(Div l r) (Div (subst l from to) (subst r from to))]
    [(Id name) (if (eq? name from) to expr)]
    [(With bound-id named-expr bound-body)
    (if (eq? bound-id from)
      expr
      (With bound-id
            named-expr
            (subst bound-body from to)))]))

(: eval : WAE -> Number)
;; evaluates WAE expressions by reducing them to numbers
(define (eval expr)
  (cases expr
    [(Num n) n]
    [(Add l r) (+ (eval l) (eval r))]
    [(Sub l r) (- (eval l) (eval r))]
    [(Mul l r) (* (eval l) (eval r))]
    [(Div l r) (/ (eval l) (eval r))]
    [(With bound-id named-expr bound-body)
    (eval (subst bound-body
                  bound-id
                  (Num (eval named-expr))))]
    [(Id name) (error 'eval "free identifier: ~s" name)]))

(: run : String -> Number)
;; evaluate a WAE program contained in a string
(define (run str)
  (eval (parse str)))

;; tests
(test (run "5") => 5)
(test (run "{+ 5 5}") => 10)
(test (run "{with {x {+ 5 5}} {+ x x}}") => 20)
(test (run "{with {x 5} {+ x x}}") => 10)
(test (run "{with {x {+ 5 5}} {with {y {- x 3}} {+ y y}}}") => 14)
(test (run "{with {x 5} {with {y {- x 3}} {+ y y}}}") => 4)
(test (run "{with {x 5} {+ x {with {x 3} 10}}}") => 15)
(test (run "{with {x 5} {+ x {with {x 3} x}}}") => 8)
(test (run "{with {x 5} {+ x {with {y 3} x}}}") => 10)
(test (run "{with {x 5} {with {y x} y}}") => 5)
(test (run "{with {x 5} {with {x x} x}}") => 5)
(test (run "{with {x 1} y}") =error> "free identifier")

Evaluation of with (contd.)Tuesday, September 25th

Oops, this program still has problems that were caught by the tests — we encounter unexpected free identifier errors. What’s the problem now? In expressions like:

{with {x 5}
  {with {y x}
    y}}

we forgot to substitute x in the expression that y is bound to. We need to the recursive substitute in both the with’s body expression as well as its named expression:

(: subst : WAE Symbol WAE -> WAE)
;; substitutes the second argument with the third argument in the
;; first argument, as per the rules of substitution; the resulting
;; expression contains no free instances of the second argument
(define (subst expr from to)
  (cases expr
    [(Num n) expr]
    [(Add l r) (Add (subst l from to) (subst r from to))]
    [(Sub l r) (Sub (subst l from to) (subst r from to))]
    [(Mul l r) (Mul (subst l from to) (subst r from to))]
    [(Div l r) (Div (subst l from to) (subst r from to))]
    [(Id name) (if (eq? name from) to expr)]
    [(With bound-id named-expr bound-body)
    (if (eq? bound-id from)
      expr
      (With bound-id
            (subst named-expr from to)      ;*** new
            (subst bound-body from to)))]))

And still we have a problem… Now it’s

{with {x 5}
  {with {x x}
    x}}

that halts with an error, but we want it to evaluate to 5! Carefully trying out our substitution code reveals the problem: when we substitute 5 for the outer x, we don’t go inside the inner with because it has the same name — but we do need to go into its named expression. We need to substitute in the named expression even if the identifier is the same one we’re substituting:

(: subst : WAE Symbol WAE -> WAE)
;; substitutes the second argument with the third argument in the
;; first argument, as per the rules of substitution; the resulting
;; expression contains no free instances of the second argument
(define (subst expr from to)
  (cases expr
    [(Num n) expr]
    [(Add l r) (Add (subst l from to) (subst r from to))]
    [(Sub l r) (Sub (subst l from to) (subst r from to))]
    [(Mul l r) (Mul (subst l from to) (subst r from to))]
    [(Div l r) (Div (subst l from to) (subst r from to))]
    [(Id name) (if (eq? name from) to expr)]
    [(With bound-id named-expr bound-body)
    (With bound-id
          (subst named-expr from to)
          (if (eq? bound-id from)
            bound-body
            (subst bound-body from to)))]))

The complete (and, finally, correct) version of the code is now:

#lang pl

#| BNF for the WAE language:
    <WAE> ::= <num>
            | { + <WAE> <WAE> }
            | { - <WAE> <WAE> }
            | { * <WAE> <WAE> }
            | { / <WAE> <WAE> }
            | { with { <id> <WAE> } <WAE> }
            | <id>
|#

;; WAE abstract syntax trees
(define-type WAE
  [Num  Number]
  [Add  WAE WAE]
  [Sub  WAE WAE]
  [Mul  WAE WAE]
  [Div  WAE WAE]
  [Id  Symbol]
  [With Symbol WAE WAE])

(: parse-sexpr : Sexpr -> WAE)
;; parses s-expressions into WAEs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(cons 'with more)
    (match sexpr
      [(list 'with (list (symbol: name) named) body)
        (With name (parse-sexpr named) (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `with' syntax in ~s" sexpr)])]
    [(list '+ lhs rhs) (Add (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '- lhs rhs) (Sub (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '* lhs rhs) (Mul (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '/ lhs rhs) (Div (parse-sexpr lhs) (parse-sexpr rhs))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

(: parse : String -> WAE)
;; parses a string containing a WAE expression to a WAE AST
(define (parse str)
  (parse-sexpr (string->sexpr str)))

#| Formal specs for `subst':
  (`N' is a <num>, `E1', `E2' are <WAE>s, `x' is some <id>,
  `y' is a *different* <id>)
      N[v/x]                = N
      {+ E1 E2}[v/x]        = {+ E1[v/x] E2[v/x]}
      {- E1 E2}[v/x]        = {- E1[v/x] E2[v/x]}
      {* E1 E2}[v/x]        = {* E1[v/x] E2[v/x]}
      {/ E1 E2}[v/x]        = {/ E1[v/x] E2[v/x]}
      y[v/x]                = y
      x[v/x]                = v
      {with {y E1} E2}[v/x] = {with {y E1[v/x]} E2[v/x]}
      {with {x E1} E2}[v/x] = {with {x E1[v/x]} E2}
|#

(: subst : WAE Symbol WAE -> WAE)
;; substitutes the second argument with the third argument in the
;; first argument, as per the rules of substitution; the resulting
;; expression contains no free instances of the second argument
(define (subst expr from to)
  (cases expr
    [(Num n) expr]
    [(Add l r) (Add (subst l from to) (subst r from to))]
    [(Sub l r) (Sub (subst l from to) (subst r from to))]
    [(Mul l r) (Mul (subst l from to) (subst r from to))]
    [(Div l r) (Div (subst l from to) (subst r from to))]
    [(Id name) (if (eq? name from) to expr)]
    [(With bound-id named-expr bound-body)
    (With bound-id
          (subst named-expr from to)
          (if (eq? bound-id from)
            bound-body
            (subst bound-body from to)))]))

#| Formal specs for `eval':
    eval(N)        = N
    eval({+ E1 E2}) = eval(E1) + eval(E2)
    eval({- E1 E2}) = eval(E1) - eval(E2)
    eval({* E1 E2}) = eval(E1) * eval(E2)
    eval({/ E1 E2}) = eval(E1) / eval(E2)
    eval(id)        = error!
    eval({with {x E1} E2}) = eval(E2[eval(E1)/x])
|#

(: eval : WAE -> Number)
;; evaluates WAE expressions by reducing them to numbers
(define (eval expr)
  (cases expr
    [(Num n) n]
    [(Add l r) (+ (eval l) (eval r))]
    [(Sub l r) (- (eval l) (eval r))]
    [(Mul l r) (* (eval l) (eval r))]
    [(Div l r) (/ (eval l) (eval r))]
    [(With bound-id named-expr bound-body)
    (eval (subst bound-body
                  bound-id
                  (Num (eval named-expr))))]
    [(Id name) (error 'eval "free identifier: ~s" name)]))

(: run : String -> Number)
;; evaluate a WAE program contained in a string
(define (run str)
  (eval (parse str)))

;; tests
(test (run "5") => 5)
(test (run "{+ 5 5}") => 10)
(test (run "{with {x 5} {+ x x}}") => 10)
(test (run "{with {x {+ 5 5}} {+ x x}}") => 20)
(test (run "{with {x 5} {with {y {- x 3}} {+ y y}}}") => 4)
(test (run "{with {x {+ 5 5}} {with {y {- x 3}} {+ y y}}}") => 14)
(test (run "{with {x 5} {+ x {with {x 3} 10}}}") => 15)
(test (run "{with {x 5} {+ x {with {x 3} x}}}") => 8)
(test (run "{with {x 5} {+ x {with {y 3} x}}}") => 10)
(test (run "{with {x 5} {with {y x} y}}") => 5)
(test (run "{with {x 5} {with {x x} x}}") => 5)
(test (run "{with {x 1} y}") =error> "free identifier")

Reminder:

Formal SpecsTuesday, September 25th

Note the formal definitions that were included in the WAE code. They are ways of describing pieces of our language that are more formal than plain English, but still not as formal (and as verbose) as the actual code.

A formal definition of subst:

(N is a <num>, E1, E2 are <WAE>s, x is some <id>, y is a different <id>)

N[v/x]                = N

{+ E1 E2}[v/x]        = {+ E1[v/x] E2[v/x]}

{- E1 E2}[v/x]        = {- E1[v/x] E2[v/x]}

{* E1 E2}[v/x]        = {* E1[v/x] E2[v/x]}

{/ E1 E2}[v/x]        = {/ E1[v/x] E2[v/x]}

y[v/x]                = y
x[v/x]                = v

{with {y E1} E2}[v/x] = {with {y E1[v/x]} E2[v/x]}
{with {x E1} E2}[v/x] = {with {x E1[v/x]} E2}

And a formal definition of eval:

eval(N)        = N

eval({+ E1 E2}) = eval(E1) + eval(E2)

eval({- E1 E2}) = eval(E1) - eval(E2)

eval({* E1 E2}) = eval(E1) * eval(E2)

eval({/ E1 E2}) = eval(E1) / eval(E2)

eval(id)        = error!

eval({with {x E1} E2}) = eval(E2[eval(E1)/x])

Lazy vs Eager EvaluationTuesday, September 25th

As we have previously seen, there are two basic approaches for evaluation: either eager or lazy. In lazy evaluation, bindings are used for sort of textual references — it is only for avoiding writing an expression twice, but the associated computation is done twice anyway. In eager evaluation, we eliminate not only the textual redundancy, but also the computation.

Which evaluation method did our evaluator use? The relevant piece of formalism is the treatment of with:

eval({with {x E1} E2}) = eval(E2[eval(E1)/x])

And the matching piece of code is:

[(With bound-id named-expr bound-body)
(eval (subst bound-body
              bound-id
              (Num (eval named-expr))))]

How do we make this lazy?

In the formal equation:

eval({with {x E1} E2}) = eval(E2[E1/x])

and in the code:

(: eval : WAE -> Number)
;; evaluates WAE expressions by reducing them to numbers
(define (eval expr)
  (cases expr
    [(Num n) n]
    [(Add l r) (+ (eval l) (eval r))]
    [(Sub l r) (- (eval l) (eval r))]
    [(Mul l r) (* (eval l) (eval r))]
    [(With bound-id named-expr bound-body)
    (eval (subst bound-body
                  bound-id
                  named-expr))] ;*** no eval and no Num wrapping
    [(Id name) (error 'eval "free identifier: ~s" name)]))

We can verify the way this works by tracing eval (compare the trace you get for the two versions):

> (trace eval) ; (put this in the definitions window)
> (run "{with {x {+ 1 2}} {* x x}}")

Ignoring the traces for now, the modified WAE interpreter works as before, specifically, all tests pass. So the question is whether the language we get is actually different than the one we had before. One difference is in execution speed, but we can’t really notice a difference, and we care more about meaning. Is there any program that will run differently in the two languages?

The main feature of the lazy evaluator is that it is not evaluating the named expression until it is actually needed. As we have seen, this leads to duplicating computations if the bound identifier is used more than once — meaning that it does not eliminate the dynamic redundancy. But what if the bound identifier is not used at all? In that case the named expression simply evaporates. This is a good hint at an expression that behaves differently in the two languages — if we add division to both languages, we get a different result when we try running:

{with {x {/ 8 0}} 7}

The eager evaluator stops with an error when it tries evaluating the division — and the lazy evaluator simply ignores it.

Even without division, we get a similar behavior for

{with {x y} 7}

but it is questionable whether the fact that this evaluates to 7 is correct behavior — we really want to forbid program that use free variable.

Furthermore, there is an issue with name capturing — we don’t want to substitute an expression into a context that captures some of its free variables. But our substitution allows just that, which is usually not a problem because by the time we do the substitution, the named expression should not have free variables that need to be replaced. However, consider evaluating this program:

{with {y x}
  {with {x 2}
    {+ x y}}}

under the two evaluation regimens: the eager version stops with an error, and the lazy version succeed. This points at a bug in our substitution, or rather not dealing with an issue that we do not encounter.

So the summary is: as long as the initial program is correct, both evaluation regimens produce the same results. If a program contains free variables, they might get captured in a naive lazy evaluator implementation (but this is a bug that should be fixed). Also, there are some cases where eager evaluation runs into a run-time problem which does not happen in a lazy evaluator because the expression is not used. It is possible to prove that when you evaluate an expression, if there is an error that can be avoided, lazy evaluation will always avoid it, whereas an eager evaluator will always run into it. On the other hand, lazy evaluators are usually slower than eager evaluator, so it’s a speed vs. robustness trade-off.

Note that with lazy evaluation we say that an identifier is bound to an expression rather than a value. (Again, this is why the eager version needed to wrap eval‘s result in a Num and this one doesn’t.)

(It is possible to change things and get a more well behaved substitution, we basically will need to find if a capture might happen, and rename things to avoid it. For example,

{with {y E1} E2}[v/x]
  if `x' and `y' are equal
    = {with {y E1[v/x]} E2} = {with {x E1[v/x]} E2}
  if `y' has a free occurrence in `v'
    = {with {y1 E1[v/x]} E2[y1/y][v/x]} ; `y1' is "fresh"
  otherwise
    = {with {x E1[v/x]} E2[v/x]}

With this, we might have gone through this path in evaluating the above:

{with {y x} {with {x 2} {+ x y}}}
{with {x₁ 2} {+ x₁ x}} ; note that x₁ is a fresh name, not x
{+ 2 x}
error: free `x`

But you can see that this is much more complicated (more code: requires a free-in predicate, being able to invent new fresh names, etc). And it’s not even the end of that story…)

de Bruijn IndexesTuesday, September 25th

This whole story revolves around names, specifically, name capture is a problem that should always be avoided (it is one major source of PL headaches).

But are names the only way we can use bindings?

There is a least one alternative way: note that the only thing we used names for are for references. We don’t really care what the name is, which is pretty obvious when we consider the two WAE expressions:

{with {x 5} {+ x x}}
{with {y 5} {+ y y}}

or the two Racket function definitions:

(define (foo x) (list x x))
(define (foo y) (list y y))

Both of these show a pair of expressions that we should consider as equal in some sense (this is called “alpha-equality”). The only thing we care about is what variable points where: the binding structure is the only thing that matters. In other words, as long as DrRacket produces the same arrows when we use Check Syntax, we consider the program to be the same, regardless of name choices (for argument names and local names, not for global names like foo in the above).

The alternative idea uses this principle: if all we care about is where the arrows go, then simply get rid of the names… Instead of referencing a binding through its name, just specify which of the surrounding scopes we want to refer to. For example, instead of:

{with {x 5} {with {y 6} {+ x y}}}

we can use a new “reference” syntax — [N] — and use this instead of the above:

{with 5 {with 6 {+ [1] [0]}}}

So the rules for [N] are — [0] is the value bound in the current scope, [1] is the value from the next one up etc.

Of course, to do this translation, we have to know the precise scope rules. Two more complicated examples:

{with {x 5} {+ x {with {y 6} {+ x y}}}}

is translated to:

{with 5 {+ [0] {with 6 {+ [1] [0]}}}}

(note how x appears as a different reference based on where it appeared in the original code.) Even more subtle:

{with {x 5} {with {y {+ x 1}} {+ x y}}}

is translated to:

{with 5 {with {+ [0] 1} {+ [1] [0]}}}

because the inner with does not have its own named expression in its scope, so the named expression is immediately in the scope of the outer with.

This is called “de Bruijn Indexes”: instead of referencing identifiers by their name, we use an index into the surrounding binding context. The major disadvantage, as can be seen in the above examples, is that it is not convenient for humans to work with. Specifically, the same identifier is referenced using different numbers, which makes it hard to understand what some code is doing. After all, abstractions are the main thing we deal with when we write programs, and having labels make the bindings structure much easier to understand than scope counts.

However, practically all compilers use this for compiled code (think about stack pointers). For example, GCC compiles this code:

{
  int x = 5;
  {
    int y = x + 1;
    return x + y;
  }
}

to:

subl $8, %esp
movl $5, -4(%ebp)  ; int x = 5
movl -4(%ebp), %eax
incl %eax
movl %eax, -8(%ebp) ; int y = %eax
movl -8(%ebp), %eax
addl -4(%ebp), %eax

Functions & Function ValuesTuesday, October 2nd

PLAI §4

Now that we have a form for local bindings, which forced us to deal with proper substitutions and everything that is related, we can get to functions. The concept of a function is itself very close to substitution, and to our with form. For example, when we write:

{with {x 5}
  {* x x}}

then the {* x x} body is itself parametrized over some value for x. If we take this expression and take out the 5, we’re left with something that has all of the necessary ingredients of a function — a bunch of code that is parameterized over some input identifier:

{with {x}
  {* x x}}

We only need to replace with and use a proper name that indicates that it’s a function:

{fun {x}
  {* x x}}

Now we have a new form in our language, one that should have a function as its meaning. As we have seen in the case of with expressions, we also need a new form to use these functions. We will use call for this, so that

{call {fun {x} {* x x}}
      5}

will be the same as the original with expression that we started with — the fun expression is like the with expression with no value, and applying it on 5 is providing that value back:

{with {x 5}
  {* x x}}

Of course, this does not help much — all we get is a way to use local bindings that is more verbose from what we started with. What we’re really missing is a way to name these functions. If we get the right evaluation rules, we can evaluate a fun expression to some value — which will allow us to bind it to a variable using with. Something like this:

{with {sqr {fun {x} {* x x}}}
  {+ {call sqr 5}
    {call sqr 6}}}

In this expression, we say that x is the formal parameter (or argument), and the 5 and 6 are actual parameters (sometimes abbreviated as formals and actuals). Note that naming functions often helps, but many times there are small functions that are fine to specify without a name — for example, consider a two-stage addition function, where there is no apparent good name for the returned function:

{with {add {fun {x}
            {fun {y}
              {+ x y}}}}
  {call {call add 8} 9}}

Implementing First Class FunctionsTuesday, October 2nd

PLAI §6 (uses some stuff from PLAI §5, which we do later)

This is a simple plan, but it is directly related to how functions are going to be used in our language. We know that {call {fun {x} E1} E2} is equivalent to a with expression, but the new thing here is that we do allow writing just the {fun ...} expression by itself, and therefore we need to have some meaning for it. The meaning, or the value of this expression, should roughly be “an expression that needs a value to be plugged in for x”. In other words, our language will have these new kinds of values that contain an expression to be evaluated later on.

There are three basic approaches that classify programming languages in relation to how the deal with functions:

  1. First order: functions are not real values. They cannot be used or returned as values by other functions. This means that they cannot be stored in data structures. This is what most “conventional” languages used to have in the past. (You will be implementing such a language in homework 4.)

    An example of such a language is the Beginner Student language that is used in HtDP, where the language is intentionally first-order to help students write correct code (at the early stages where using a function as a value is usually an error). It’s hard to find practical modern languages that fall in this category.

  2. Higher order: functions can receive and return other functions as values. This is what you get with C and modern Fortran.

  3. First class: functions are values with all the rights of other values. In particular, they can be supplied to other functions, returned from functions, stored in data structures, and new functions can be created at run-time. (And most modern languages have first class functions.)

The last category is the most interesting one. Back in the old days, complex expressions were not first-class in that they could not be freely composed. This is still the case in machine-code: as we’ve seen earlier, to compute an expression such as

(-b + sqrt(b^2 - 4*a*c)) / 2a

you have to do something like this:

x = b * b
y = 4 * a
y = y * c
x = x - y
x = sqrt(x)
y = -b
x = y + x
y = 2 * a
s = x / y

In other words, every intermediate value needs to have its own name. But with proper (“high-level”) programming languages (at least most of them…) you can just write the original expression, with no names for these values.

With first-class functions something similar happens — it is possible to have complex expressions that consume and return functions, and they do not need to be named.

What we get with our fun expression (if we can make it work) is exactly this: it generates a function, and you can choose to either bind it to a name, or not. The important thing is that the value exists independently of a name.

This has a major effect on the “personality” of a programming language as we will see. In fact, just adding this feature will make our language much more advanced than languages with just higher-order or first-order functions.


Quick Example: the following is working JavaScript code, that uses first class functions.

function foo(x) {
  function bar(y) { return x + y; }
  return bar;
}
function main() {
  var f = foo(1);
  var g = foo(10);
  return [f(2), g(2)];
}

Note that the above definition of foo does not use an anonymous “lambda expression” — in Racket terms, it’s translated to

(define (foo x)
  (define (bar y) (+ x y))
  bar)

The returned function is not anonymous, but it’s not really named either: the bar name is bound only inside the body of foo, and outside of it that name no longer exists since it’s not its scope. It gets used in the printed form if the function value is displayed, but this is merely a debugging aid. The anonymous lambda version that is common in Racket can be used in JavaScript too:

function foo(x) {
  return function(y) { return x + y; }
}

Side-note: GCC includes extensions that allow internal function definitions, but it still does not have first class functions — trying to do the above is broken:

#include <stdio.h>
typedef int(*int2int)(int);
int2int foo(int x) {
  int bar(int y) { return x + y; }
  return bar;
}
int main() {
  int2int f = foo(1);
  int2int g = foo(10);
  printf(">> %d, %d\n", f(2), g(2));
}

The FLANG LanguageTuesday, October 2nd

Now for the implementation — we call this new language FLANG.

First, the BNF:

<FLANG> ::= <num>
          | { + <FLANG> <FLANG> }
          | { - <FLANG> <FLANG> }
          | { * <FLANG> <FLANG> }
          | { / <FLANG> <FLANG> }
          | { with { <id> <FLANG> } <FLANG> }
          | <id>
          | { fun { <id> } <FLANG> }
          | { call <FLANG> <FLANG> }

And the matching type definition:

(define-type FLANG
  [Num  Number]
  [Add  FLANG FLANG]
  [Sub  FLANG FLANG]
  [Mul  FLANG FLANG]
  [Div  FLANG FLANG]
  [Id  Symbol]
  [With Symbol FLANG FLANG]
  [Fun  Symbol      FLANG] ; No named-expression
  [Call FLANG FLANG])

The parser for this grammar is, as usual, straightforward:

(: parse-sexpr : Sexpr -> FLANG)
;; parses s-expressions into FLANGs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(cons 'with more)
    (match sexpr
      [(list 'with (list (symbol: name) named) body)
        (With name (parse-sexpr named) (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `with' syntax in ~s" sexpr)])]
    [(cons 'fun more)
    (match sexpr
      [(list 'fun (list (symbol: name)) body)
        (Fun name (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `fun' syntax in ~s" sexpr)])]
    [(list '+ lhs rhs) (Add (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '- lhs rhs) (Sub (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '* lhs rhs) (Mul (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '/ lhs rhs) (Div (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list 'call fun arg)
                      (Call (parse-sexpr fun) (parse-sexpr arg))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

We also need to patch up the substitution function to deal with these things. The scoping rule for the new function form is, unsurprisingly, similar to the rule of with, except that there is no extra expression now, and the scoping rule for call is the same as for the arithmetic operators:

N[v/x]                = N

{+ E1 E2}[v/x]        = {+ E1[v/x] E2[v/x]}

{- E1 E2}[v/x]        = {- E1[v/x] E2[v/x]}

{* E1 E2}[v/x]        = {* E1[v/x] E2[v/x]}

{/ E1 E2}[v/x]        = {/ E1[v/x] E2[v/x]}

y[v/x]                = y
x[v/x]                = v

{with {y E1} E2}[v/x] = {with {y E1[v/x]} E2[v/x]}
{with {x E1} E2}[v/x] = {with {x E1[v/x]} E2}

{call E1 E2}[v/x]    = {call E1[v/x] E2[v/x]}

{fun {y} E}[v/x]      = {fun {y} E[v/x]}
{fun {x} E}[v/x]      = {fun {x} E}

And the matching code:

(: subst : FLANG Symbol FLANG -> FLANG)
;; substitutes the second argument with the third argument in the
;; first argument, as per the rules of substitution; the resulting
;; expression contains no free instances of the second argument
(define (subst expr from to)
  (cases expr
    [(Num n) expr]
    [(Add l r) (Add (subst l from to) (subst r from to))]
    [(Sub l r) (Sub (subst l from to) (subst r from to))]
    [(Mul l r) (Mul (subst l from to) (subst r from to))]
    [(Div l r) (Div (subst l from to) (subst r from to))]
    [(Id name) (if (eq? name from) to expr)]
    [(With bound-id named-expr bound-body)
    (With bound-id
          (subst named-expr from to)
          (if (eq? bound-id from)
            bound-body
            (subst bound-body from to)))]
    [(Call l r) (Call (subst l from to) (subst r from to))]
    [(Fun bound-id bound-body)
    (if (eq? bound-id from)
      expr
      (Fun bound-id (subst bound-body from to)))]))

Now, before we start working on an evaluator, we need to decide on what exactly do we use to represent values of this language. Before we had functions, we had only number values and we used Racket numbers to represent them. Now we have two kinds of values — numbers and functions. It seems easy enough to continue using Racket numbers to represent numbers, but what about functions? What should be the result of evaluating

{fun {x} {+ x 1}}

? Well, this is the new toy we have: it should be a function value, which is something that can be used just like numbers, but instead of arithmetic operations, we can call these things. What we need is a way to avoid evaluating the body expression of the function — delay it — and instead use some value that will contain this delayed expression in a way that can be used later.

To accommodate this, we will change our implementation strategy a little: we will use our syntax objects for numbers ((Num n) instead of just n), which will be a little inconvenient when we do the arithmetic operations, but it will simplify life by making it possible to evaluate functions in a similar way: simply return their own syntax object as their values. The syntax object has what we need: the body expression that needs to be evaluated later when the function is called, and it also has the identifier name that should be replaced with the actual input to the function call. This means that evaluating:

(Add (Num 1) (Num 2))

now yields

(Num 3)

and a number (Num 5) evaluates to (Num 5).

In a similar way, (Fun 'x (Num 2)) evaluates to (Fun 'x (Num 2)).

Why would this work? Well, because call will be very similar to with — the only difference is that its arguments are ordered a little differently, being retrieved from the function that is applied and the argument.

The formal evaluation rules are therefore treating functions like numbers, and use the syntax object to represent both values:

eval(N)        = N

eval({+ E1 E2}) = eval(E1) + eval(E2)

eval({- E1 E2}) = eval(E1) - eval(E2)

eval({* E1 E2}) = eval(E1) * eval(E2)

eval({/ E1 E2}) = eval(E1) / eval(E2)

eval(id)        = error!

eval({with {x E1} E2}) = eval(E2[eval(E1)/x])

eval(FUN)      = FUN ; assuming FUN is a function expression

eval({call E1 E2})
                = eval(Ef[eval(E2)/x])  if eval(E1) = {fun {x} Ef}
                = error!                otherwise

Note that the last rule could be written using a translation to a with expression:

eval({call E1 E2})
                = eval({with {x E2} Ef}) if eval(E1) = {fun {x} Ef}
                = error!                otherwise

And alternatively, we could specify with using call and fun:

eval({with {x E1} E2}) = eval({call {fun {x} E2} E1})

There is a small problem in these rules which is intuitively seen by the fact that the evaluation rule for a call is expected to be very similar to the one for arithmetic operations. We now have two kinds of values, so we need to check the arithmetic operation’s arguments too:

eval({+ E1 E2}) = N1 + N2
                    if eval(E1), eval(E2) evaluate to numbers N1, N2
                    otherwise error!
...

The corresponding code is:

(: eval : FLANG -> FLANG)                      ;*** note return type
;; evaluates FLANG expressions by reducing them to *expressions* but
;; only expressions that stand for values: only `Fun`s and `Num`s
(define (eval expr)
  (cases expr
    [(Num n) expr]                            ;*** change here
    [(Add l r) (arith-op + (eval l) (eval r))]
    [(Sub l r) (arith-op - (eval l) (eval r))]
    [(Mul l r) (arith-op * (eval l) (eval r))]
    [(Div l r) (arith-op / (eval l) (eval r))]
    [(With bound-id named-expr bound-body)
    (eval (subst bound-body
                  bound-id
                  (eval named-expr)))]        ;*** no `(Num ...)'
    [(Id name) (error 'eval "free identifier: ~s" name)]
    [(Fun bound-id bound-body) expr]          ;*** similar to `Num'
    [(Call (Fun bound-id bound-body) arg-expr) ;*** nested pattern
    (eval (subst bound-body                  ;*** just like `with'
                  bound-id
                  (eval arg-expr)))]
    [(Call something arg-expr)
    (error 'eval "`call' expects a function, got: ~s" something)]))

Note that the Call case is doing the same thing we do in the With case. In fact, we could have just generated a With expression and evaluate that instead:

    ...
    [(Call (Fun bound-id bound-body) arg-expr)
    (eval (With bound-id arg-expr bound-body))]
    ...

The arith-op function is in charge of checking that the input values are numbers (represented as FLANG numbers), translating them to plain numbers, performing the Racket operation, then re-wrapping the result in a Num. Note how its type indicates that it is a higher-order function.

(: arith-op : (Number Number -> Number) FLANG FLANG -> FLANG)
;; gets a Racket numeric binary operator, and uses it within a FLANG
;; `Num' wrapper (note the H.O type)
(define (arith-op op expr1 expr2)
  (Num (op (Num->number expr1) (Num->number expr2))))

It uses the following function to convert FLANG numbers to Racket numbers. (Note that else is almost always a bad idea since it can prevent the compiler from showing you places to edit code — but this case is an exception since we never want to deal with anything other than Nums.) The reason that this function is relatively trivial is that we chose the easy way and represented numbers using Racket numbers, but we could have used strings or anything else.

(: Num->number : FLANG -> Number)
;; convert a FLANG number to a Racket one
(define (Num->number e)
  (cases e
    [(Num n) n]
    [else (error 'arith-op "expected a number, got: ~s" e)]))

We can also make things a little easier to use if we make run convert the result to a number:

(: run : String -> Number)
;; evaluate a FLANG program contained in a string
(define (run str)
  (let ([result (eval (parse str))])
    (cases result
      [(Num n) n]
      [else (error 'run "evaluation returned a non-number: ~s"
                  result)])))

Adding few simple tests we get:

;; The Flang interpreter

#lang pl

#|
The grammar:
  <FLANG> ::= <num>
            | { + <FLANG> <FLANG> }
            | { - <FLANG> <FLANG> }
            | { * <FLANG> <FLANG> }
            | { / <FLANG> <FLANG> }
            | { with { <id> <FLANG> } <FLANG> }
            | <id>
            | { fun { <id> } <FLANG> }
            | { call <FLANG> <FLANG> }

Evaluation rules:

  subst:
    N[v/x]                = N
    {+ E1 E2}[v/x]        = {+ E1[v/x] E2[v/x]}
    {- E1 E2}[v/x]        = {- E1[v/x] E2[v/x]}
    {* E1 E2}[v/x]        = {* E1[v/x] E2[v/x]}
    {/ E1 E2}[v/x]        = {/ E1[v/x] E2[v/x]}
    y[v/x]                = y
    x[v/x]                = v
    {with {y E1} E2}[v/x] = {with {y E1[v/x]} E2[v/x]} ; if y =/= x
    {with {x E1} E2}[v/x] = {with {x E1[v/x]} E2}
    {call E1 E2}[v/x]    = {call E1[v/x] E2[v/x]}
    {fun {y} E}[v/x]      = {fun {y} E[v/x]}          ; if y =/= x
    {fun {x} E}[v/x]      = {fun {x} E}

  eval:
    eval(N)            = N
    eval({+ E1 E2})    = eval(E1) + eval(E2)  \ if both E1 and E2
    eval({- E1 E2})    = eval(E1) - eval(E2)  \ evaluate to numbers
    eval({* E1 E2})    = eval(E1) * eval(E2)  / otherwise error!
    eval({/ E1 E2})    = eval(E1) / eval(E2)  /
    eval(id)          = error!
    eval({with {x E1} E2}) = eval(E2[eval(E1)/x])
    eval(FUN)          = FUN ; assuming FUN is a function expression
    eval({call E1 E2}) = eval(Ef[eval(E2)/x])
                          if eval(E1)={fun {x} Ef}, otherwise error!
|#

(define-type FLANG
  [Num  Number]
  [Add  FLANG FLANG]
  [Sub  FLANG FLANG]
  [Mul  FLANG FLANG]
  [Div  FLANG FLANG]
  [Id  Symbol]
  [With Symbol FLANG FLANG]
  [Fun  Symbol FLANG]
  [Call FLANG FLANG])

(: parse-sexpr : Sexpr -> FLANG)
;; parses s-expressions into FLANGs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(cons 'with more)
    (match sexpr
      [(list 'with (list (symbol: name) named) body)
        (With name (parse-sexpr named) (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `with' syntax in ~s" sexpr)])]
    [(cons 'fun more)
    (match sexpr
      [(list 'fun (list (symbol: name)) body)
        (Fun name (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `fun' syntax in ~s" sexpr)])]
    [(list '+ lhs rhs) (Add (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '- lhs rhs) (Sub (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '* lhs rhs) (Mul (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '/ lhs rhs) (Div (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list 'call fun arg)
                      (Call (parse-sexpr fun) (parse-sexpr arg))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

(: parse : String -> FLANG)
;; parses a string containing a FLANG expression to a FLANG AST
(define (parse str)
  (parse-sexpr (string->sexpr str)))

(: subst : FLANG Symbol FLANG -> FLANG)
;; substitutes the second argument with the third argument in the
;; first argument, as per the rules of substitution; the resulting
;; expression contains no free instances of the second argument
(define (subst expr from to)
  (cases expr
    [(Num n) expr]
    [(Add l r) (Add (subst l from to) (subst r from to))]
    [(Sub l r) (Sub (subst l from to) (subst r from to))]
    [(Mul l r) (Mul (subst l from to) (subst r from to))]
    [(Div l r) (Div (subst l from to) (subst r from to))]
    [(Id name) (if (eq? name from) to expr)]
    [(With bound-id named-expr bound-body)
    (With bound-id
          (subst named-expr from to)
          (if (eq? bound-id from)
            bound-body
            (subst bound-body from to)))]
    [(Call l r) (Call (subst l from to) (subst r from to))]
    [(Fun bound-id bound-body)
    (if (eq? bound-id from)
      expr
      (Fun bound-id (subst bound-body from to)))]))

(: Num->number : FLANG -> Number)
;; convert a FLANG number to a Racket one
(define (Num->number e)
  (cases e
    [(Num n) n]
    [else (error 'arith-op "expected a number, got: ~s" e)]))

(: arith-op : (Number Number -> Number) FLANG FLANG -> FLANG)
;; gets a Racket numeric binary operator, and uses it within a FLANG
;; `Num' wrapper
(define (arith-op op expr1 expr2)
  (Num (op (Num->number expr1) (Num->number expr2))))

(: eval : FLANG -> FLANG)
;; evaluates FLANG expressions by reducing them to *expressions*
(define (eval expr)
  (cases expr
    [(Num n) expr]
    [(Add l r) (arith-op + (eval l) (eval r))]
    [(Sub l r) (arith-op - (eval l) (eval r))]
    [(Mul l r) (arith-op * (eval l) (eval r))]
    [(Div l r) (arith-op / (eval l) (eval r))]
    [(With bound-id named-expr bound-body)
    (eval (subst bound-body
                  bound-id
                  (eval named-expr)))]
    [(Id name) (error 'eval "free identifier: ~s" name)]
    [(Fun bound-id bound-body) expr]
    [(Call (Fun bound-id bound-body) arg-expr)
    (eval (subst bound-body
                  bound-id
                  (eval arg-expr)))]
    [(Call something arg-expr)
    (error 'eval "`call' expects a function, got: ~s" something)]))

(: run : String -> Number)
;; evaluate a FLANG program contained in a string
(define (run str)
  (let ([result (eval (parse str))])
    (cases result
      [(Num n) n]
      [else (error 'run "evaluation returned a non-number: ~s"
                  result)])))

;; tests
(test (run "{call {fun {x} {+ x 1}} 4}")
      => 5)
(test (run "{with {add3 {fun {x} {+ x 3}}}
              {call add3 1}}")
      => 4)
(test (run "{with {add3 {fun {x} {+ x 3}}}
              {with {add1 {fun {x} {+ x 1}}}
                {with {x 3}
                  {call add1 {call add3 x}}}}}")
      => 7)

There is still a problem with this version. First a question — if call is similar to arithmetic operations (and to with in what it actually does), then how come the code is different enough that it doesn’t even need an auxiliary function?

Second question: what should happen if we evaluate these code snippets:

(run "{with {add {fun {x}
                  {fun {y}
                    {+ x y}}}}
      {call {call add 8} 9}}")
(run "{with {identity {fun {x} x}}
        {with {foo {fun {x} {+ x 1}}}
          {call {call identity foo} 123}}}")
(run "{call {call {fun {x} {call x 1}}
                  {fun {x} {fun {y} {+ x y}}}}
            123}")

Third question, what will happen if we do the above?

What we’re missing is an evaluation of the function expression, in case it’s not a literal fun form. The following fixes this:

(: eval : FLANG -> FLANG)
;; evaluates FLANG expressions by reducing them to *expressions*
(define (eval expr)
  (cases expr
    [(Num n) expr]
    [(Add l r) (arith-op + (eval l) (eval r))]
    [(Sub l r) (arith-op - (eval l) (eval r))]
    [(Mul l r) (arith-op * (eval l) (eval r))]
    [(Div l r) (arith-op / (eval l) (eval r))]
    [(With bound-id named-expr bound-body)
    (eval (subst bound-body
                  bound-id
                  (eval named-expr)))]
    [(Id name) (error 'eval "free identifier: ~s" name)]
    [(Fun bound-id bound-body) expr]
    [(Call fun-expr arg-expr)
    (let ([fval (eval fun-expr)])      ;*** need to evaluate this!
      (cases fval
        [(Fun bound-id bound-body)
          (eval (subst bound-body
                      bound-id
                      (eval arg-expr)))]
        [else (error 'eval "`call' expects a function, got: ~s"
                            fval)]))]))

The complete code is:

;; The Flang interpreter

#lang pl

#|
The grammar:
  <FLANG> ::= <num>
            | { + <FLANG> <FLANG> }
            | { - <FLANG> <FLANG> }
            | { * <FLANG> <FLANG> }
            | { / <FLANG> <FLANG> }
            | { with { <id> <FLANG> } <FLANG> }
            | <id>
            | { fun { <id> } <FLANG> }
            | { call <FLANG> <FLANG> }

Evaluation rules:

  subst:
    N[v/x]                = N
    {+ E1 E2}[v/x]        = {+ E1[v/x] E2[v/x]}
    {- E1 E2}[v/x]        = {- E1[v/x] E2[v/x]}
    {* E1 E2}[v/x]        = {* E1[v/x] E2[v/x]}
    {/ E1 E2}[v/x]        = {/ E1[v/x] E2[v/x]}
    y[v/x]                = y
    x[v/x]                = v
    {with {y E1} E2}[v/x] = {with {y E1[v/x]} E2[v/x]} ; if y =/= x
    {with {x E1} E2}[v/x] = {with {x E1[v/x]} E2}
    {call E1 E2}[v/x]    = {call E1[v/x] E2[v/x]}
    {fun {y} E}[v/x]      = {fun {y} E[v/x]}          ; if y =/= x
    {fun {x} E}[v/x]      = {fun {x} E}

  eval:
    eval(N)            = N
    eval({+ E1 E2})    = eval(E1) + eval(E2)  \ if both E1 and E2
    eval({- E1 E2})    = eval(E1) - eval(E2)  \ evaluate to numbers
    eval({* E1 E2})    = eval(E1) * eval(E2)  / otherwise error!
    eval({/ E1 E2})    = eval(E1) / eval(E2)  /
    eval(id)          = error!
    eval({with {x E1} E2}) = eval(E2[eval(E1)/x])
    eval(FUN)          = FUN ; assuming FUN is a function expression
    eval({call E1 E2}) = eval(Ef[eval(E2)/x])
                          if eval(E1)={fun {x} Ef}, otherwise error!
|#

(define-type FLANG
  [Num  Number]
  [Add  FLANG FLANG]
  [Sub  FLANG FLANG]
  [Mul  FLANG FLANG]
  [Div  FLANG FLANG]
  [Id  Symbol]
  [With Symbol FLANG FLANG]
  [Fun  Symbol FLANG]
  [Call FLANG FLANG])

(: parse-sexpr : Sexpr -> FLANG)
;; parses s-expressions into FLANGs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(cons 'with more)
    (match sexpr
      [(list 'with (list (symbol: name) named) body)
        (With name (parse-sexpr named) (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `with' syntax in ~s" sexpr)])]
    [(cons 'fun more)
    (match sexpr
      [(list 'fun (list (symbol: name)) body)
        (Fun name (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `fun' syntax in ~s" sexpr)])]
    [(list '+ lhs rhs) (Add  (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '- lhs rhs) (Sub  (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '* lhs rhs) (Mul  (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '/ lhs rhs) (Div  (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list 'call fun arg)
                      (Call (parse-sexpr fun) (parse-sexpr arg))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

(: parse : String -> FLANG)
;; parses a string containing a FLANG expression to a FLANG AST
(define (parse str)
  (parse-sexpr (string->sexpr str)))

(: subst : FLANG Symbol FLANG -> FLANG)
;; substitutes the second argument with the third argument in the
;; first argument, as per the rules of substitution; the resulting
;; expression contains no free instances of the second argument
(define (subst expr from to)
  (cases expr
    [(Num n) expr]
    [(Add l r) (Add (subst l from to) (subst r from to))]
    [(Sub l r) (Sub (subst l from to) (subst r from to))]
    [(Mul l r) (Mul (subst l from to) (subst r from to))]
    [(Div l r) (Div (subst l from to) (subst r from to))]
    [(Id name) (if (eq? name from) to expr)]
    [(With bound-id named-expr bound-body)
    (With bound-id
          (subst named-expr from to)
          (if (eq? bound-id from)
            bound-body
            (subst bound-body from to)))]
    [(Call l r) (Call (subst l from to) (subst r from to))]
    [(Fun bound-id bound-body)
    (if (eq? bound-id from)
      expr
      (Fun bound-id (subst bound-body from to)))]))

(: Num->number : FLANG -> Number)
;; convert a FLANG number to a Racket one
(define (Num->number e)
  (cases e
    [(Num n) n]
    [else (error 'arith-op "expected a number, got: ~s" e)]))

(: arith-op : (Number Number -> Number) FLANG FLANG -> FLANG)
;; gets a Racket numeric binary operator, and uses it within a FLANG
;; `Num' wrapper
(define (arith-op op expr1 expr2)
  (Num (op (Num->number expr1) (Num->number expr2))))

(: eval : FLANG -> FLANG)
;; evaluates FLANG expressions by reducing them to *expressions*
(define (eval expr)
  (cases expr
    [(Num n) expr]
    [(Add l r) (arith-op + (eval l) (eval r))]
    [(Sub l r) (arith-op - (eval l) (eval r))]
    [(Mul l r) (arith-op * (eval l) (eval r))]
    [(Div l r) (arith-op / (eval l) (eval r))]
    [(With bound-id named-expr bound-body)
    (eval (subst bound-body
                  bound-id
                  (eval named-expr)))]
    [(Id name) (error 'eval "free identifier: ~s" name)]
    [(Fun bound-id bound-body) expr]
    [(Call fun-expr arg-expr)
    (let ([fval (eval fun-expr)])
      (cases fval
        [(Fun bound-id bound-body)
          (eval (subst bound-body
                      bound-id
                      (eval arg-expr)))]
        [else (error 'eval "`call' expects a function, got: ~s"
                            fval)]))]))

(: run : String -> Number)
;; evaluate a FLANG program contained in a string
(define (run str)
  (let ([result (eval (parse str))])
    (cases result
      [(Num n) n]
      [else (error 'run "evaluation returned a non-number: ~s"
                  result)])))

;; tests
(test (run "{call {fun {x} {+ x 1}} 4}")
      => 5)
(test (run "{with {add3 {fun {x} {+ x 3}}}
              {call add3 1}}")
      => 4)
(test (run "{with {add3 {fun {x} {+ x 3}}}
              {with {add1 {fun {x} {+ x 1}}}
                {with {x 3}
                  {call add1 {call add3 x}}}}}")
      => 7)
(test (run "{with {add {fun {x}
                        {fun {y}
                          {+ x y}}}}
              {call {call add 8} 9}}")
      => 17)
(test (run "{with {identity {fun {x} x}}
              {with {foo {fun {x} {+ x 1}}}
                {call {call identity foo} 123}}}")
      => 124)
(test (run "{call {call {fun {x} {call x 1}}
                        {fun {x} {fun {y} {+ x y}}}}
                  123}")
      => 124)

Introducing Racket’s lambdaTuesday, October 2nd

fun & lambda difference between lambda and simple values not being able to do recursive functions with let let* as a derived form let with lambda in Racket –> can be a derived form how if can be used to implement and and or as derived forms

Newtonian syntax vs. a lambda expression.

Don’t be fooled into making a bogus connection between Racket’s syntax, and its unique powers… The fact is that it is not the only language that has this capability. For example, this:

(define (f g) (g 2 3))
(f +) ==> 5
(f *) ==> 6
(f (lambda (x y) (+ (square x) (square y)))) ==> 13

Can be written in JavaScript like this:

function f(g) { return g(2,3); }
function square(x) { return x*x; }
console.log(f(function (x,y) { return square(x) + square(y); }));

or in ES6 JavaScript:

let f = (g) => g(2,3);
let square = (x) => x*x;
console.log(f((x,y) => square(x) + square(y)));

In Perl:

sub f { my ($g) = @_; return $g->(2,3); }
sub square { my ($x) = @_; return $x * $x; }
print f(sub { my ($x, $y) = @_; return square($x) + square($y); });

In Ruby:

def f(g) g.call(2,3) end
def square(x) x*x end
puts f(lambda{|x,y| square(x) + square(y)})

etc. Even Java has lambda expressions, and recently C++ added them too.

Using Functions as ObjectsTuesday, October 2nd

A very important aspect of Racket — using “higher order” functions — functions that get and return functions. Here is a very simple example:

(define (f x) (lambda () x))
(define a (f 2))
(a)  -->  2
(define b (f 3))
(b)  -->  3

Note: what we get is actually an object that remembers (by the substitution we’re doing) a number. How about:

(define aa (f a))
(aa)    -->  #<procedure> (this is a)
((aa))  -->  2

Take this idea to the next level:

(define (kons x y)
  (lambda (b)
    (if b x y)))
(define (kar p) (p #t))
(define (kdr p) (p #f))
(define a (kons 1 2))
(define b (kons 3 4))
(list (kar a) (kdr a))
(list (kar b) (kdr b))

Or, with types:

(: kons : (All (A B) A B -> (Boolean -> (U A B))))
(define (kons x y)
  (lambda (b)
    (if b x y)))
(: kar : (All (T) (Boolean -> T) -> T))
(define (kar p) (p #t))
(: kdr : (All (T) (Boolean -> T) -> T))
(define (kdr p) (p #f))
(define a (kons 1 2))
(define b (kons 3 4))
(list (kar a) (kdr a))
(list (kar b) (kdr b))

Even more — why should the internal function expect a boolean and choose what to return? We can simply expect a function that will take the two values and return one:

(define (kons x y) (lambda (s) (s x y)))
(define (kar p) (p (lambda (x y) x)))
(define (kdr p) (p (lambda (x y) y)))
(define a (kons 1 2))
(define b (kons 3 4))
(list (kar a) (kdr a))
(list (kar b) (kdr b))

And a typed version, using our own constructor to make it a little less painful:

(define-type (Kons A B) = ((A B -> (U A B)) -> (U A B)))

(: kons : (All (A B) A B -> (Kons A B)))
(define (kons x y) (lambda (s) (s x y)))
(: kar : (All (A B) (Kons A B) -> (U A B)))
(define (kar p) (p (lambda (x y) x)))
(: kdr : (All (A B) (Kons A B) -> (U A B)))
(define (kdr p) (p (lambda (x y) y)))
(define a (kons 1 2))
(define b (kons 3 4))
(list (kar a) (kdr a))
(list (kar b) (kdr b))

Note that the Kons type definition is the same as:

(define-type Kons = (All (A B) (A B -> (U A B)) -> (U A B)))

so All is to polymorphic type definitions what lambda is for function definitions.

Finally in JavaScript:

function kons(x,y) { return function(s) { return s(x, y); } }
function kar(p) { return p(function(x,y){ return x; }); }
function kdr(p) { return p(function(x,y){ return y; }); }
a = kons(1,2);
b = kons(3,4);
console.log('a = <' + kar(a) + ',' + kdr(a) + '>' );
console.log('b = <' + kar(b) + ',' + kdr(b) + '>' );

Or with ES6 arrow functions, the function definitionss become:

var kons = (x,y) => s => s(x,y);
var kar  = p => p((x,y) => x);
var kdr  = p => p((x,y) => y);

CurryingTuesday, October 2nd

A curried function is a function that, instead of accepting two (or more) arguments, accepts only one and returns a function that accepts the rest. For example:

(: plus : Number -> (Number -> Number))
(define (plus x)
  (lambda (y)
    (+ x y)))

It’s easy to write functions for translating between normal and curried versions.

(define (currify f)
  (lambda (x)
    (lambda (y)
      (f x y))))

Typed version of that, with examples:

(: currify : (All (A B C) (A B -> C) -> (A -> (B -> C))))
;; convert a double-argument function to a curried one
(define (currify f)
  (lambda (x) (lambda (y) (f x y))))

(: add : Number Number -> Number)
(define (add x y) (+ x y))

(: plus : Number -> (Number -> Number))
(define plus (currify add))

(test ((plus 1) 2) => 3)
(test (((currify add) 1) 2) => 3)
(test (map (plus 1) '(1 2 3)) => '(2 3 4))
(test (map ((currify add) 1) '(1 2 3)) => '(2 3 4))
(test (map ((currify +) 1) '(1 2 3)) => '(2 3 4))

Usages — common with H.O. functions like map, where we want to fix one argument.

When dealing with such higher-order code, the types are very helpful, since every arrow corresponds to a function:

(: currify : (All (A B C) (A B -> C) -> (A -> (B -> C))))

It is common to make the -> function type associate to the right, so you can find this type written as:

currify : (A B -> C) -> (A -> B -> C)

or even as

currify : (A B -> C) -> A -> B -> C

but that can be a little confusing…

Using Higher-Order & Anonymous FunctionsTuesday, October 2nd

Say that we have a function for estimating derivatives of a function at a specific point:

(define dx 0.01)

(: deriv : (Number -> Number) Number -> Number)
;; compute the derivative of `f' at the given point `x'
(define (deriv f x)
  (/ (- (f (+ x dx)) (f x)) dx))

(: integrate : (Number -> Number) Number -> Number)
;; compute an integral of `f' at the given point `x'
(define (integrate f x)
  (: loop : Number Number -> Number)
  (define (loop y acc)
    (if (> y x)
      (* acc dx)
      (loop (+ y dx) (+ acc (f y)))))
  (loop 0 0))

And say that we want to try out various functions given some plot function that draws graphs of numeric functions, for example:

(plot sin)

The problem is that plot expects a single (Number -> Number) function — if we want to try it with a derivative, we can do this:

(: sin-deriv : Number -> Number)
;; the derivative of sin
(define sin-deriv (lambda (x) (deriv sin x)))
(plot sin-deriv)

But this will get very tedious very fast — it is much simpler to use an anonymous function:

(plot (lambda (x) (deriv sin x)))

we can even verify that our derivative is correct by comparing a known function to its derivative

(plot (lambda (x) (- (deriv sin x) (cos x))))

But it’s still not completely natural to do these things — you need to explicitly combine functions, which is not too convenient. Instead of doing this, we can write H.O. functions that will work with functional inputs and outputs. For example, we can write a function to subtract functions:

(: fsub : (Number -> Number) (Number -> Number)
          -> (Number -> Number))
;; subtracts two numeric 1-argument functions
(define (fsub f g)
  (lambda (x) (- (f x) (g x))))

and the same for the derivative:

(: fderiv : (Number -> Number) -> (Number -> Number))
;; compute the derivative function of `f'
(define (fderiv f)
  (lambda (x) (deriv f x)))

Now we can try the same in a much easier way:

(plot (fsub (fderiv sin) cos))

More than that — our fderiv could be created from deriv automatically:

(: currify : (All (A B C) (A B -> C) -> (A -> B -> C)))
;; convert a double-argument function to a curried one
(define (currify f)
  (lambda (x) (lambda (y) (f x y))))

(: fderiv : (Number -> Number) -> (Number -> Number))
;; compute the derivative function of `f'
(define fderiv (currify deriv))

Same principle with fsub: we can write a function that converts a binary arithmetical function into a function that operates on unary numeric function. But to make things more readable we can define new types for unary and binary numeric functions:

(define-type UnaryFun  = (Number -> Number))
(define-type BinaryFun = (Number Number -> Number))

(: binop->fbinop : BinaryFun -> (UnaryFun UnaryFun -> UnaryFun))
;; turns an arithmetic binary operator to a function operator
(define (binop->fbinop op)
  (lambda (f g)
    (lambda (x) (op (f x) (g x)))))

(: fsub : UnaryFun UnaryFun -> UnaryFun)
;; functional pointwise subtraction
(define fsub (binop->fbinop -))

We can do this with anything — developing a rich library of functions and functionals (functions over functions) is extremely easy… Here’s a pretty extensive yet very short library of functions:

#lang pl untyped

(define (currify f)
  (lambda (x) (lambda (y) (f x y))))
(define (binop->fbinop op)
  (lambda (f g)
    (lambda (x) (op (f x) (g x)))))
(define (compose f g)
  (lambda (x) (f (g x))))

(define dx 0.01)
(define (deriv f x)
  (/ (- (f (+ x dx)) (f x)) dx))
(define (integrate f x)
  (define over? (if (< x 0) < >))
  (define step  (if (< x 0) - +))
  (define add  (if (< x 0) - +))
  (define (loop y acc)
    (if (over y x)
      (/ acc dx)
      (loop (step y dx) (add acc (f y)))))
  (loop 0 0))

(define fadd (binop->fbinop +))
(define fsub (binop->fbinop -))
(define fmul (binop->fbinop *))
(define fdiv (binop->fbinop /))
(define fderiv    (currify deriv))
(define fintegrate (currify integrate))
;; ...

This is written in the “untyped dialect” of the class language, but it should be easy now to add the types.

Examples:

;; want to verify that `integrate' is the opposite of `deriv':
;;  take a function, subtract it from its derivative's integral
(plot (fsub sin (fintegrate (fderiv sin))))

;; want to magnify the errors? -- here's how you magnify:
(plot (compose ((currify *) 5) sin))

;; so:
(plot (compose ((currify *) 20)
              (fsub sin (fintegrate (fderiv sin)))))

Side-note: “Point-Free” combinatorsTuesday, October 2nd

Forming functions without using lambda (or an implicit lambda using a define syntactic sugar) is called point-free style. It’s especially popular in Haskell, where it is easier to form functions this way because of implicit currying and a large number of higher level function combinators. If used too much, it can easily lead to obfuscated code.


This is not Runtime Code GenerationTuesday, October 2nd

All of this is similar to run-time code generation, but not really. The only thing that fderiv does is take a function and store it somewhere in the returned function, then when that function receives a number, it uses the stored function and send it to deriv with the number. We could simply write deriv as what fderiv is — which is the real derivative function:

(define (deriv f)
  (lambda (x)
    (/ (- (f (+ x dx)) (f x)) dx)))

but again, this is not faster or slower than the plain deriv. However, there are some situations where we can do some of the computation on the first-stage argument, saving work from the second stage. Here is a cooked-to-exaggeration example — we want a function that receives two inputs x, y and returns fib(x)*y, but we must use a stupid fib:

(define (fib n)
  (if (<= n 1)
    n
    (+ (fib (- n 1)) (fib (- n 2)))))

The function we want is:

(define (bogus x y)
  (* (fib x) y))

If we currify it as usual (or just use currify), we get:

(define (bogus x)
  (lambda (y)
    (* (fib x) y)))

And try this several times:

(define bogus24 (bogus 24))
(map bogus24 '(1 2 3 4 5))

But in the definition of bogus, notice that (fib x) does not depend on y — so we can rewrite it a little differently:

(define (bogus x)
  (let ([fibx (fib x)])
    (lambda (y)
      (* fibx y))))

and trying the above again is much faster now:

(define bogus24 (bogus 24))
(map bogus24 '(1 2 3 4 5))

This is therefore not doing any kind of runtime code generation, but it enables doing similar optimizations in our code. A proper RTCG facility would recompile the curried function for a given first input, and (hopefully) automatically achieve the optimization that we did in a manual way.

Substitution CachesTuesday, October 2nd

PLAI §5 (called “deferred substitutions” there)

Evaluating using substitutions is very inefficient — at each scope, we copy a piece of the program AST. This includes all function calls which implies an impractical cost (function calls should be cheap!).

To get over this, we want to use a cache of substitutions.

Basic idea: we begin evaluating with no cached substitutions, then collect them as we encounter bindings.

Implies another change for our evaluator: we don’t really substitute cache at that point.

Implementation of Cache FunctionalityTuesday, October 2nd

First, we need a type for a substitution cache. For this we will use a list of lists of two elements each — a name and its value FLANG:

;; a type for substitution caches:
(define-type SubstCache = (Listof (List Symbol FLANG)))

We need to have an empty substitution cache, a way to extend it, and a way to look things up:

(: empty-subst : SubstCache)
(define empty-subst null)

(: extend : Symbol FLANG SubstCache -> SubstCache)
;; extend a given substitution cache with a new mapping
(define (extend id expr sc)
  (cons (list id expr) sc))

(: lookup : Symbol SubstCache -> FLANG)
;; lookup a symbol in a substitution cache, return the value it is
;; bound to (or throw an error if it isn't bound)
(define (lookup name sc)
  (cond [(null? sc) (error 'lookup "no binding for ~s" name)]
        [(eq? name (first (first sc))) (second (first sc))]
        [else (lookup name (rest sc))]))

Actually, the reason to use such list of lists is that Racket has a built-in function called assq that will do this kind of search (assq is a search in an association list using eq? for the key comparison). This is a version of lookup that uses assq:

(define (lookup name sc)
  (let ([cell (assq name sc)])
    (if cell
      (second cell)
      (error 'lookup "no binding for ~s" name))))

Formal Rules for Cached SubstitutionsTuesday, October 2nd

The formal evaluation rules are now different. Evaluation carries along a substitution cache that begins its life as empty: so eval needs an extra argument. We begin by writing the rules that deal with the cache, and use the above function names for simplicity — the behavior of the three definitions can be summed up in a single rule for lookup:

lookup(x,empty-subst)    = error!
lookup(x,extend(x,E,sc))  = E
lookup(x,extend(y,E,sc))  = lookup(x,sc)  if `x' is not `y'

And now we can write the new rules for eval

eval(N,sc)                = N
eval({+ E1 E2},sc)        = eval(E1,sc) + eval(E2,sc)
eval({- E1 E2},sc)        = eval(E1,sc) - eval(E2,sc)
eval({* E1 E2},sc)        = eval(E1,sc) * eval(E2,sc)
eval({/ E1 E2},sc)        = eval(E1,sc) / eval(E2,sc)
eval(x,sc)                = lookup(x,sc)
eval({with {x E1} E2},sc) = eval(E2,extend(x,eval(E1,sc),sc))
eval({fun {x} E},sc)      = {fun {x} E}
eval({call E1 E2},sc)
        = eval(Ef,extend(x,eval(E2,sc),sc))
                          if eval(E1,sc) = {fun {x} Ef}
        = error!          otherwise

Note that there is no mention of subst — the whole point is that we don’t really do substitution, but use the cache instead. The lookup rules, and the places where extend is used replaces subst, and therefore specifies our scoping rules.

Also note that the rule for call is still very similar to the rule for with, but it looks like we have lost something — the interesting bit with substituting into fun expressions.

Evaluating with Substitution CachesTuesday, October 2nd

Implementing the new eval is easy now — it is extended in the same way that the formal eval rule is extended:

(: eval : FLANG SubstCache -> FLANG)
;; evaluates FLANG expressions by reducing them to expressions
(define (eval expr sc)
  (cases expr
    [(Num n) expr]
    [(Add l r) (arith-op + (eval l sc) (eval r sc))]
    [(Sub l r) (arith-op - (eval l sc) (eval r sc))]
    [(Mul l r) (arith-op * (eval l sc) (eval r sc))]
    [(Div l r) (arith-op / (eval l sc) (eval r sc))]
    [(With bound-id named-expr bound-body)
    (eval bound-body
          (extend bound-id (eval named-expr sc) sc))]
    [(Id name) (lookup name sc)]
    [(Fun bound-id bound-body) expr]
    [(Call fun-expr arg-expr)
    (let ([fval (eval fun-expr sc)])
      (cases fval
        [(Fun bound-id bound-body)
          (eval bound-body
                (extend bound-id (eval arg-expr sc) sc))]
        [else (error 'eval "`call' expects a function, got: ~s"
                            fval)]))]))

Again, note that we don’t need subst anymore, but the rest of the code (the data type definition, parsing, and arith-op) is exactly the same.

Finally, we need to make sure that eval is initially called with an empty cache. This is easy to change in our main run entry point:

(: run : String -> Number)
;; evaluate a FLANG program contained in a string
(define (run str)
  (let ([result (eval (parse str) empty-subst)])
    (cases result
      [(Num n) n]
      [else (error 'run "evaluation returned a non-number: ~s"
                  result)])))

The full code (including the same tests, but not including formal rules for now) follows. Note that one test does not pass.

#lang pl

(define-type FLANG
  [Num  Number]
  [Add  FLANG FLANG]
  [Sub  FLANG FLANG]
  [Mul  FLANG FLANG]
  [Div  FLANG FLANG]
  [Id  Symbol]
  [With Symbol FLANG FLANG]
  [Fun  Symbol FLANG]
  [Call FLANG FLANG])

(: parse-sexpr : Sexpr -> FLANG)
;; parses s-expressions into FLANGs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(cons 'with more)
    (match sexpr
      [(list 'with (list (symbol: name) named) body)
        (With name (parse-sexpr named) (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `with' syntax in ~s" sexpr)])]
    [(cons 'fun more)
    (match sexpr
      [(list 'fun (list (symbol: name)) body)
        (Fun name (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `fun' syntax in ~s" sexpr)])]
    [(list '+ lhs rhs) (Add (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '- lhs rhs) (Sub (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '* lhs rhs) (Mul (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '/ lhs rhs) (Div (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list 'call fun arg)
                      (Call (parse-sexpr fun) (parse-sexpr arg))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

(: parse : String -> FLANG)
;; parses a string containing a FLANG expression to a FLANG AST
(define (parse str)
  (parse-sexpr (string->sexpr str)))

;; a type for substitution caches:
(define-type SubstCache = (Listof (List Symbol FLANG)))

(: empty-subst : SubstCache)
(define empty-subst null)

(: extend : Symbol FLANG SubstCache -> SubstCache)
;; extend a given substitution cache with a new mapping
(define (extend name val sc)
  (cons (list name val) sc))

(: lookup : Symbol SubstCache -> FLANG)
;; lookup a symbol in a substitution cache, return the value it is
;; bound to (or throw an error if it isn't bound)
(define (lookup name sc)
  (let ([cell (assq name sc)])
    (if cell
      (second cell)
      (error 'lookup "no binding for ~s" name))))

(: Num->number : FLANG -> Number)
;; convert a FLANG number to a Racket one
(define (Num->number e)
  (cases e
    [(Num n) n]
    [else (error 'arith-op "expected a number, got: ~s" e)]))

(: arith-op : (Number Number -> Number) FLANG FLANG -> FLANG)
;; gets a Racket numeric binary operator, and uses it within a FLANG
;; `Num' wrapper
(define (arith-op op expr1 expr2)
  (Num (op (Num->number expr1) (Num->number expr2))))

(: eval : FLANG SubstCache -> FLANG)
;; evaluates FLANG expressions by reducing them to expressions
(define (eval expr sc)
  (cases expr
    [(Num n) expr]
    [(Add l r) (arith-op + (eval l sc) (eval r sc))]
    [(Sub l r) (arith-op - (eval l sc) (eval r sc))]
    [(Mul l r) (arith-op * (eval l sc) (eval r sc))]
    [(Div l r) (arith-op / (eval l sc) (eval r sc))]
    [(With bound-id named-expr bound-body)
    (eval bound-body
          (extend bound-id (eval named-expr sc) sc))]
    [(Id name) (lookup name sc)]
    [(Fun bound-id bound-body) expr]
    [(Call fun-expr arg-expr)
    (let ([fval (eval fun-expr sc)])
      (cases fval
        [(Fun bound-id bound-body)
          (eval bound-body
                (extend bound-id (eval arg-expr sc) sc))]
        [else (error 'eval "`call' expects a function, got: ~s"
                            fval)]))]))

(: run : String -> Number)
;; evaluate a FLANG program contained in a string
(define (run str)
  (let ([result (eval (parse str) empty-subst)])
    (cases result
      [(Num n) n]
      [else (error 'run "evaluation returned a non-number: ~s"
                  result)])))

;; tests
(test (run "{call {fun {x} {+ x 1}} 4}")
      => 5)
(test (run "{with {add3 {fun {x} {+ x 3}}}
              {call add3 1}}")
      => 4)
(test (run "{with {add3 {fun {x} {+ x 3}}}
              {with {add1 {fun {x} {+ x 1}}}
                {with {x 3}
                  {call add1 {call add3 x}}}}}")
      => 7)
(test (run "{with {identity {fun {x} x}}
              {with {foo {fun {x} {+ x 1}}}
                {call {call identity foo} 123}}}")
      => 124)
(test (run "{call {with {x 3}
                    {fun {y} {+ x y}}}
                  4}")
      => 7)
(test (run "{with {f {with {x 3} {fun {y} {+ x y}}}}
              {with {x 100}
                {call f 4}}}")
      => 7)
(test (run "{with {x 3}
              {with {f {fun {y} {+ x y}}}
                {with {x 5}
                  {call f 4}}}}")
      => "???")
(test (run "{call {call {fun {x} {call x 1}}
                        {fun {x} {fun {y} {+ x y}}}}
                  123}")
      => 124)

Dynamic and Lexical ScopesTuesday, October 9th

This seems like it should work, and it even worked on a few examples, except for one which was hard to follow. Seems like we have a bug…

Now we get to a tricky issue that managed to be a problem for lots of language implementors, including the first version of Lisp. Lets try to run the following expression — try to figure out what it will evaluate to:

(run "{with {x 3}
        {with {f {fun {y} {+ x y}}}
          {with {x 5}
            {call f 4}}}}")

We expect it to return 7 (at least I do!), but we get 9 instead… The question is — should it return 9?

What we have arrived to is called dynamic scope. Scope is determined by the dynamic run-time environment (which is represented by our substitution cache). This is almost always undesirable, as I hope to convince you.

Before we start, we define two options for a programming language:

Racket uses lexical scope, our new evaluator uses dynamic, the old substitution-based evaluator was static etc.

As a side-remark, Lisp began its life as a dynamically-scoped language. The artifacts of this were (sort-of) dismissed as an implementation bug. When Scheme was introduced, it was the first Lisp dialect that used strictly lexical scoping, and Racket is obviously doing the same. (Some Lisp implementations used dynamic scope for interpreted code and lexical scope for compiled code!) In fact, Emacs Lisp is the only live dialects of Lisp that is still dynamically scoped by default. To see this, compare a version of the above code in Racket:

(let ((x 3))
  (let ((f (lambda (y) (+ x y))))
    (let ((x 5))
      (f 4))))

and the Emacs Lisp version (which looks almost the same):

(let ((x 3))
  (let ((f (lambda (y) (+ x y))))
    (let ((x 5))
      (funcall f 4))))

which also happens when we use another function on the way:

(defun blah (func val)
  (funcall func val))

(let ((x 3))
  (let ((f (lambda (y) (+ x y))))
    (let ((x 5))
      (blah f 4))))

and note that renaming identifiers can lead to different code — change that val to x:

(defun blah (func x)
  (funcall func x))

(let ((x 3))
  (let ((f (lambda (y) (+ x y))))
    (let ((x 5))
      (blah f 4))))

and you get 8 because the argument name changed the x that the internal function sees!

Consider also this Emacs Lisp function:

(defun return-x ()
  x)

which has no meaning by itself (x is unbound),

(return-x)

but can be given a dynamic meaning using a let:

(let ((x 5)) (return-x))

or a function application:

(defun foo (x)
  (return-x))

(foo 5)

There is also a dynamically-scoped language in the course languages:

#lang pl dynamic

(define x 123)

(define (getx) x)

(define (bar1 x) (getx))
(define (bar2 y) (getx))

(test (getx) => 123)
(test (let ([x 456]) (getx)) => 456)
(test (getx) => 123)
(test (bar1 999) => 999)
(test (bar2 999) => 123)

(define (foo x) (define (helper) (+ x 1)) helper)
(test ((foo 0)) => 124)

;; and *much* worse:
(define (add x y) (+ x y))
(test (let ([+ *]) (add 6 7)) => 42)

Note how bad the last example gets: you basically cannot call any function and know in advance what it will do.

There are some cases where dynamic scope can be useful in that it allows you to “remotely” customize any piece of code. A good example of where this is taken to an extreme is Emacs: originally, it was based on an ancient Lisp dialect that was still dynamically scoped, but it retained this feature even when practically all Lisp dialects moved on to having lexical scope by default. The reason for this is that the danger of dynamic scope is also a way to make a very open system where almost anything can be customized by changing it “remotely”. Here’s a concrete example for a similar kind of dynamic scope usage that makes a very hackable and open system:

#lang pl dynamic

(define tax% 6.25)
(define (with-tax n)
  (+ n (* n (/ tax% 100))))

(with-tax 10) ; how much do we pay?
(let ([tax% 18.0]) (with-tax 10)) ; how much would we pay in Israel?

;; make that into a function
(define il-tax% 18.0)
(define (us-over-il-saving n)
  (- (let ([tax% il-tax%]) (with-tax n))
    (with-tax n)))

(us-over-il-saving 10)
;; can even control that: how much would we save if
;; the tax in israel went down one percent?
(let ([il-tax% (- il-tax% 1)]) (us-over-il-saving 10))

;; or change both: how much savings in NH instead of MA?
(let ((tax% 0.0) (il-tax% tax%)) (us-over-il-saving 1000))

Obviously, this power to customize everything is also the main source of problems with getting no guarantees for code. A common way to get the best of both worlds is to have controllable dynamic scope. For example, Common Lisp also has lexical scope everywhere by default, but some variables can be declared as special, which means that they are dynamically scoped. The main problem with that is that you can’t tell when a variable is special by just looking at the code that uses it, so a more popular approach is the one that is used in Racket: all bindings are always lexically scoped, but there are parameters which are a kind of dynamically scoped value containers — but they are bound to plain (lexically scoped) identifiers. Here’s the same code as above, translated to Racket with parameters:

#lang racket

(define tax% (make-parameter 6.5))  ; create the dynamic container
(define (with-tax n)
  (+ n (* n (/ (tax%) 100))))      ; note how its value is accessed

(with-tax 10) ; how much do we pay?
(parameterize ([tax% 18.0]) (with-tax 10)) ; not a `let'

;; make that into a function
(define il-tax% (make-parameter 18.0))
(define (us-over-il-saving n)
  (- (parameterize ([tax% (il-tax%)]) (with-tax n))
    (with-tax n)))

(us-over-il-saving 10)
(parameterize ([il-tax% (- (il-tax%) 1)]) (us-over-il-saving 10))

The main point here is that the points where a dynamically scoped value is used are under the programmer’s control — you cannot “customize” what - is doing, for example. This gives us back the guarantees that we like to have (= that code works), but of course these points are pre-determined, unlike an environment where everything can be customized including things that are unexpectedly useful.

As a side-note, after many decades of debating this, Emacs has finally added lexical scope in its core language, but this is still determined by a flag — a global lexical-binding variable.

Dynamic versus Lexical ScopeTuesday, October 9th

And back to the discussion of whether we should use dynamic or lexical scope:

Implementing Lexical Scope: Closures and EnvironmentsTuesday, October 9th

So how do we fix this?

Lets go back to the root of the problem: the new evaluator does not behave in the same way as the substituting evaluator. In the old evaluator, it was easy to see how functions can behave as objects that remember values. For example, when we do this:

{with {x 1}
  {fun {y}
    {+ x y}}}

the result was a function value, which actually was the syntax object for this:

{fun {y} {+ 1 y}}

Now if we call this function from someplace else like:

{with {f {with {x 1} {fun {y} {+ x y}}}}
  {with {x 2}
    {call f 3}}}

it is clear what the result will be: f is bound to a function that adds 1 to its input, so in the above the later binding for x has no effect at all.

But with the caching evaluator, the value of

{with {x 1}
  {fun {y}
    {+ x y}}}

is simply:

{fun {y} {+ x y}}

and there is no place where we save the 1 — that’s the root of our problem. (That’s also what makes people suspect that using lambda in Racket and any other functional language involves some inefficient code-recompiling magic.) In fact, we can verify that by inspecting the returned value, and see that it does contain a free identifier.

Clearly, we need to create an object that contains the body and the argument list, like the function syntax object — but we don’t do any substitution, so in addition to the body an argument name(s) we need to remember that we still need to substitute x by 1 . This means that the pieces of information we need to know are:

- formal argument(s):    {y}
- body:                  {+ x y}
- pending substitutions: [1/x]

and that last bit has the missing 1. The resulting object is called a closure because it closes the function body over the substitutions that are still pending (its environment).

So, the first change is in the value of functions which now need all these pieces, unlike the Fun case for the syntax object.

A second place that needs changing is the when functions are called. When we’re done evaluating the call arguments (the function value and the argument value) but before we apply the function we have two values — there is no more use for the current substitution cache at this point: we have finished dealing with all substitutions that were necessary over the current expression — we now continue with evaluating the body of the function, with the new substitutions for the formal arguments and actual values given. But the body itself is the same one we had before — which is the previous body with its suspended substitutions that we still did not do.

Rewrite the evaluation rules — all are the same except for evaluating a fun form and a call form:

eval(N,sc)                = N
eval({+ E1 E2},sc)        = eval(E1,sc) + eval(E2,sc)
eval({- E1 E2},sc)        = eval(E1,sc) - eval(E2,sc)
eval({* E1 E2},sc)        = eval(E1,sc) * eval(E2,sc)
eval({/ E1 E2},sc)        = eval(E1,sc) / eval(E2,sc)
eval(x,sc)                = lookup(x,sc)
eval({with {x E1} E2},sc) = eval(E2,extend(x,eval(E1,sc),sc))
eval({fun {x} E},sc)      = <{fun {x} E}, sc>
eval({call E1 E2},sc1)
        = eval(Ef,extend(x,eval(E2,sc1),sc2))
                          if eval(E1,sc1) = <{fun {x} Ef}, sc2>
        = error!          otherwise

As a side note, these substitution caches are a little more than “just a cache” now — they actually hold an environment of substitutions in which expression should be evaluated. So we will switch to the common environment name now.:

eval(N,env)                = N
eval({+ E1 E2},env)        = eval(E1,env) + eval(E2,env)
eval({- E1 E2},env)        = eval(E1,env) - eval(E2,env)
eval({* E1 E2},env)        = eval(E1,env) * eval(E2,env)
eval({/ E1 E2},env)        = eval(E1,env) / eval(E2,env)
eval(x,env)                = lookup(x,env)
eval({with {x E1} E2},env) = eval(E2,extend(x,eval(E1,env),env))
eval({fun {x} E},env)      = <{fun {x} E}, env>
eval({call E1 E2},env1)
        = eval(Ef,extend(x,eval(E2, env1),env2))
                          if eval(E1,env1) = <{fun {x} Ef}, env2>
        = error!          otherwise

In case you find this easier to follow, the “flat algorithm” for evaluating a call is:

1. f := evaluate E1 in env1
2. if f is not a <{fun ...},...> closure then error!
3. x := evaluate E2 in env1
4. new_env := extend env_of(f) by mapping arg_of(f) to x
5. evaluate (and return) body_of(f) in new_env

Note how the scoping rules that are implied by this definition match the scoping rules that were implied by the substitution-based rules. (It should be possible to prove that they are the same.)

The changes to the code are almost trivial, except that we need a way to represent <{fun {x} Ef}, env> pairs.


The implication of this change is that we now cannot use the same type for function syntax and function values since function values have more than just syntax. There is a simple solution to this — we never do any substitutions now, so we don’t need to translate values into expressions — we can come up with a new type for values, separate from the type of abstract syntax trees.

When we do this, we will also fix our hack of using FLANG as the type of values: this was merely a convenience since the AST type had cases for all kinds of values that we needed. (In fact, you should have noticed that Racket does this too: numbers, strings, booleans, etc are all used by both programs and syntax representation (s-expressions) — but note that function values are not used in syntax.) We will now implement a separate VAL type for runtime values.

First, we need now a type for such environments — we can use Listof for this:

;; a type for environments:
(define-type ENV = (Listof (List Symbol VAL)))

but we can just as well define a new type for environment values:

(define-type ENV
  [EmptyEnv]
  [Extend Symbol VAL ENV])

Reimplementing lookup is now simple:

(: lookup : Symbol ENV -> VAL)
;; lookup a symbol in an environment, return its value or throw an
;; error if it isn't bound
(define (lookup name env)
  (cases env
    [(EmptyEnv) (error 'lookup "no binding for ~s" name)]
    [(Extend id val rest-env)
    (if (eq? id name) val (lookup name rest-env))]))

… we don’t need extend because we get Extend from the type definition, and we also get (EmptyEnv) instead of empty-subst.

We now use this with the new type for values — two variants of these:

(define-type VAL
  [NumV Number]
  [FunV Symbol FLANG ENV]) ; arg-name, body, scope

And now the new implementation of eval which uses the new type and implements lexical scope:

(: eval : FLANG ENV -> VAL)
;; evaluates FLANG expressions by reducing them to values
(define (eval expr env)
  (cases expr
    [(Num n) (NumV n)]
    [(Add l r) (arith-op + (eval l env) (eval r env))]
    [(Sub l r) (arith-op - (eval l env) (eval r env))]
    [(Mul l r) (arith-op * (eval l env) (eval r env))]
    [(Div l r) (arith-op / (eval l env) (eval r env))]
    [(With bound-id named-expr bound-body)
    (eval bound-body
          (Extend bound-id (eval named-expr env) env))]
    [(Id name) (lookup name env)]
    [(Fun bound-id bound-body)
    (FunV bound-id bound-body env)]
    [(Call fun-expr arg-expr)
    (let ([fval (eval fun-expr env)])
      (cases fval
        [(FunV bound-id bound-body f-env)
          (eval bound-body
                (Extend bound-id (eval arg-expr env) f-env))]
        [else (error 'eval "`call' expects a function, got: ~s"
                            fval)]))]))

We also need to update arith-op to use VAL objects. The full code follows — it now passes all tests, including the example that we used to find the problem.

;; The Flang interpreter, using environments

#lang pl

#|
The grammar:
  <FLANG> ::= <num>
            | { + <FLANG> <FLANG> }
            | { - <FLANG> <FLANG> }
            | { * <FLANG> <FLANG> }
            | { / <FLANG> <FLANG> }
            | { with { <id> <FLANG> } <FLANG> }
            | <id>
            | { fun { <id> } <FLANG> }
            | { call <FLANG> <FLANG> }

Evaluation rules:
  eval(N,env)                = N
  eval({+ E1 E2},env)        = eval(E1,env) + eval(E2,env)
  eval({- E1 E2},env)        = eval(E1,env) - eval(E2,env)
  eval({* E1 E2},env)        = eval(E1,env) * eval(E2,env)
  eval({/ E1 E2},env)        = eval(E1,env) / eval(E2,env)
  eval(x,env)                = lookup(x,env)
  eval({with {x E1} E2},env) = eval(E2,extend(x,eval(E1,env),env))
  eval({fun {x} E},env)      = <{fun {x} E}, env>
  eval({call E1 E2},env1)
          = eval(Ef,extend(x,eval(E2,env1),env2))
                            if eval(E1,env1) = <{fun {x} Ef}, env2>
          = error!          otherwise
|#

(define-type FLANG
  [Num  Number]
  [Add  FLANG FLANG]
  [Sub  FLANG FLANG]
  [Mul  FLANG FLANG]
  [Div  FLANG FLANG]
  [Id  Symbol]
  [With Symbol FLANG FLANG]
  [Fun  Symbol FLANG]
  [Call FLANG FLANG])

(: parse-sexpr : Sexpr -> FLANG)
;; parses s-expressions into FLANGs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(cons 'with more)
    (match sexpr
      [(list 'with (list (symbol: name) named) body)
        (With name (parse-sexpr named) (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `with' syntax in ~s" sexpr)])]
    [(cons 'fun more)
    (match sexpr
      [(list 'fun (list (symbol: name)) body)
        (Fun name (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `fun' syntax in ~s" sexpr)])]
    [(list '+ lhs rhs) (Add (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '- lhs rhs) (Sub (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '* lhs rhs) (Mul (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '/ lhs rhs) (Div (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list 'call fun arg)
                      (Call (parse-sexpr fun) (parse-sexpr arg))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

(: parse : String -> FLANG)
;; parses a string containing a FLANG expression to a FLANG AST
(define (parse str)
  (parse-sexpr (string->sexpr str)))

;; Types for environments, values, and a lookup function

(define-type ENV
  [EmptyEnv]
  [Extend Symbol VAL ENV])

(define-type VAL
  [NumV Number]
  [FunV Symbol FLANG ENV])

(: lookup : Symbol ENV -> VAL)
;; lookup a symbol in an environment, return its value or throw an
;; error if it isn't bound
(define (lookup name env)
  (cases env
    [(EmptyEnv) (error 'lookup "no binding for ~s" name)]
    [(Extend id val rest-env)
    (if (eq? id name) val (lookup name rest-env))]))

(: NumV->number : VAL -> Number)
;; convert a FLANG runtime numeric value to a Racket one
(define (NumV->number val)
  (cases val
    [(NumV n) n]
    [else (error 'arith-op "expected a number, got: ~s" val)]))

(: arith-op : (Number Number -> Number) VAL VAL -> VAL)
;; gets a Racket numeric binary operator, and uses it within a NumV
;; wrapper
(define (arith-op op val1 val2)
  (NumV (op (NumV->number val1) (NumV->number val2))))

(: eval : FLANG ENV -> VAL)
;; evaluates FLANG expressions by reducing them to values
(define (eval expr env)
  (cases expr
    [(Num n) (NumV n)]
    [(Add l r) (arith-op + (eval l env) (eval r env))]
    [(Sub l r) (arith-op - (eval l env) (eval r env))]
    [(Mul l r) (arith-op * (eval l env) (eval r env))]
    [(Div l r) (arith-op / (eval l env) (eval r env))]
    [(With bound-id named-expr bound-body)
    (eval bound-body
          (Extend bound-id (eval named-expr env) env))]
    [(Id name) (lookup name env)]
    [(Fun bound-id bound-body)
    (FunV bound-id bound-body env)]
    [(Call fun-expr arg-expr)
    (let ([fval (eval fun-expr env)])
      (cases fval
        [(FunV bound-id bound-body f-env)
          (eval bound-body
                (Extend bound-id (eval arg-expr env) f-env))]
        [else (error 'eval "`call' expects a function, got: ~s"
                            fval)]))]))

(: run : String -> Number)
;; evaluate a FLANG program contained in a string
(define (run str)
  (let ([result (eval (parse str) (EmptyEnv))])
    (cases result
      [(NumV n) n]
      [else (error 'run "evaluation returned a non-number: ~s"
                  result)])))

;; tests
(test (run "{call {fun {x} {+ x 1}} 4}")
      => 5)
(test (run "{with {add3 {fun {x} {+ x 3}}}
              {call add3 1}}")
      => 4)
(test (run "{with {add3 {fun {x} {+ x 3}}}
              {with {add1 {fun {x} {+ x 1}}}
                {with {x 3}
                  {call add1 {call add3 x}}}}}")
      => 7)
(test (run "{with {identity {fun {x} x}}
              {with {foo {fun {x} {+ x 1}}}
                {call {call identity foo} 123}}}")
      => 124)
(test (run "{with {x 3}
              {with {f {fun {y} {+ x y}}}
                {with {x 5}
                  {call f 4}}}}")
      => 7)
(test (run "{call {with {x 3}
                    {fun {y} {+ x y}}}
                  4}")
      => 7)
(test (run "{with {f {with {x 3} {fun {y} {+ x y}}}}
              {with {x 100}
                {call f 4}}}")
      => 7)
(test (run "{call {call {fun {x} {call x 1}}
                        {fun {x} {fun {y} {+ x y}}}}
                  123}")
      => 124)

Fixing an Overlooked BugTuesday, October 9th

Incidentally, this version fixes a bug we had previously in the substitution version of FLANG:

(run "{with {f {fun {y} {+ x y}}}
        {with {x 7}
          {call f 1}}}")

This bug was due to our naive subst, which doesn’t avoid capturing renames. But note that since that version of the evaluator makes its way from the outside in, there is no difference in semantics for valid programs — ones that don’t have free identifiers.

(Reminder: This was not a dynamically scoped language, just a bug that happened when x wasn’t substituted away before f was replaced with something that refers to x.)

Lexical Scope using Racket ClosuresTuesday, October 9th

PLAI §11 (without the last part about recursion)

An alternative representation for an environment.

We’ve already seen how first-class functions can be used to implement “objects” that contain some information. We can use the same idea to represent an environment. The basic intuition is — an environment is a mapping (a function) between an identifier and some value. For example, we can represent the environment that maps 'a to 1 and 'b to 2 (using just numbers for simplicity) using this function:

(: my-map : Symbol -> Number)
(define (my-map id)
  (cond [(eq? 'a id) 1]
        [(eq? 'b id) 2]
        [else (error ...)]))

An empty mapping that is implemented in this way has the same type:

(: empty-mapping : Symbol -> Number)
(define (empty-mapping id)
  (error ...))

We can use this idea to implement our environments: we only need to define three things — EmptyEnv, Extend, and lookup. If we manage to keep the contract to these functions intact, we will be able to simply plug it into the same evaluator code with no other changes. It will also be more convenient to define ENV as the appropriate function type for use in the VAL type definition instead of using the actual type:

;; Define a type for functional environments
(define-type ENV = Symbol -> VAL)

Now we get to EmptyEnv — this is expected to be a function that expects no arguments and creates an empty environment, one that behaves like the empty-mapping function defined above. We could define it like this (changing the empty-mapping type to return a VAL):

(define (EmptyEnv) empty-mapping)

but we can skip the need for an extra definition and simply return an empty mapping function:

(: EmptyEnv : -> ENV)
(define (EmptyEnv)
  (lambda (id) (error ...)))

(The un-Rackety name is to avoid replacing previous code that used the EmptyEnv name for the constructor that was created by the type definition.)

The next thing we tackle is lookup. The previous definition that was used is:

(: lookup : Symbol ENV -> VAL)
(define (lookup name env)
  (cases env
    [(EmptyEnv) (error 'lookup "no binding for ~s" name)]
    [(Extend id val rest-env)
    (if (eq? id name) val (lookup name rest-env))]))

How should it be modified now? Easy — an environment is a mapping: a Racket function that will do the searching job itself. We don’t need to modify the contract since we’re still using ENV, except a different implementation for it. The new definition is:

(: lookup : Symbol ENV -> VAL)
(define (lookup name env)
  (env name))

Note that lookup does almost nothing — it simply delegates the real work to the env argument. This is a good hint for the error message that empty mappings should throw —

(: EmptyEnv : -> ENV)
(define (EmptyEnv)
  (lambda (id) (error 'lookup "no binding for ~s" id)))

Finally, Extend — this was previously created by the variant case of the ENV type definition:

[Extend Symbol VAL ENV]

keeping the same type that is implied by this variant means that the new Extend should look like this:

(: Extend : Symbol VAL ENV -> ENV)
(define (Extend id val rest-env)
  ...)

The question is — how do we extend a given environment? Well, first, we know that the result should be mapping — a symbol -> VAL function that expects an identifier to look for:

(: Extend : Symbol VAL ENV -> ENV)
(define (Extend id val rest-env)
  (lambda (name)
    ...))

Next, we know that in the generated mapping, if we look for id then the result should be val:

(: Extend : Symbol VAL ENV -> ENV)
(define (Extend id val rest-env)
  (lambda (name)
    (if (eq? name id)
      val
      ...)))

If the name that we’re looking for is not the same as id, then we need to search through the previous environment, eg: (lookup name rest). But we know what lookup does — it simply delegates back to the mapping function (which is our rest argument), so we can take a direct route:

(: Extend : Symbol VAL ENV -> ENV)
(define (Extend id val rest-env)
  (lambda (name)
    (if (eq? name id)
      val
      (rest-env name))))

(Note that the last line is simply (lookup name rest-env), but we know that we have a functional implementation.)

To see how all this works, try out extending an empty environment a few times and examine the result. For example, the environment that we began with:

(define (my-map id)
  (cond [(eq? 'a id) 1]
        [(eq? 'b id) 2]
        [else (error ...)]))

behaves in the same way (if the type of values is numbers) as

(Extend 'a 1 (Extend 'b 2 (EmptyEnv)))

The new code is now the same, except for the environment code:

#lang pl

#|
The grammar:
  <FLANG> ::= <num>
            | { + <FLANG> <FLANG> }
            | { - <FLANG> <FLANG> }
            | { * <FLANG> <FLANG> }
            | { / <FLANG> <FLANG> }
            | { with { <id> <FLANG> } <FLANG> }
            | <id>
            | { fun { <id> } <FLANG> }
            | { call <FLANG> <FLANG> }

Evaluation rules:
  eval(N,env)                = N
  eval({+ E1 E2},env)        = eval(E1,env) + eval(E2,env)
  eval({- E1 E2},env)        = eval(E1,env) - eval(E2,env)
  eval({* E1 E2},env)        = eval(E1,env) * eval(E2,env)
  eval({/ E1 E2},env)        = eval(E1,env) / eval(E2,env)
  eval(x,env)                = lookup(x,env)
  eval({with {x E1} E2},env) = eval(E2,extend(x,eval(E1,env),env))
  eval({fun {x} E},env)      = <{fun {x} E}, env>
  eval({call E1 E2},env1)
          = eval(Ef,extend(x,eval(E2,env1),env2))
                            if eval(E1,env1) = <{fun {x} Ef}, env2>
          = error!          otherwise
|#

(define-type FLANG
  [Num  Number]
  [Add  FLANG FLANG]
  [Sub  FLANG FLANG]
  [Mul  FLANG FLANG]
  [Div  FLANG FLANG]
  [Id  Symbol]
  [With Symbol FLANG FLANG]
  [Fun  Symbol FLANG]
  [Call FLANG FLANG])

(: parse-sexpr : Sexpr -> FLANG)
;; parses s-expressions into FLANGs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(cons 'with more)
    (match sexpr
      [(list 'with (list (symbol: name) named) body)
        (With name (parse-sexpr named) (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `with' syntax in ~s" sexpr)])]
    [(cons 'fun more)
    (match sexpr
      [(list 'fun (list (symbol: name)) body)
        (Fun name (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `fun' syntax in ~s" sexpr)])]
    [(list '+ lhs rhs) (Add (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '- lhs rhs) (Sub (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '* lhs rhs) (Mul (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '/ lhs rhs) (Div (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list 'call fun arg)
                      (Call (parse-sexpr fun) (parse-sexpr arg))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

(: parse : String -> FLANG)
;; parses a string containing a FLANG expression to a FLANG AST
(define (parse str)
  (parse-sexpr (string->sexpr str)))

;; Types for environments, values, and a lookup function

(define-type VAL
  [NumV Number]
  [FunV Symbol FLANG ENV])

;; Define a type for functional environments
(define-type ENV = Symbol -> VAL)

(: EmptyEnv : -> ENV)
(define (EmptyEnv)
  (lambda (id) (error 'lookup "no binding for ~s" id)))

(: Extend : Symbol VAL ENV -> ENV)
;; extend a given environment cache with a new binding
(define (Extend id val rest-env)
  (lambda (name)
    (if (eq? name id)
      val
      (rest-env name))))

(: lookup : Symbol ENV -> VAL)
;; lookup a symbol in an environment, return its value or throw an
;; error if it isn't bound
(define (lookup name env)
  (env name))

(: NumV->number : VAL -> Number)
;; convert a FLANG runtime numeric value to a Racket one
(define (NumV->number val)
  (cases val
    [(NumV n) n]
    [else (error 'arith-op "expected a number, got: ~s" val)]))

(: arith-op : (Number Number -> Number) VAL VAL -> VAL)
;; gets a Racket numeric binary operator, and uses it within a NumV
;; wrapper
(define (arith-op op val1 val2)
  (NumV (op (NumV->number val1) (NumV->number val2))))

(: eval : FLANG ENV -> VAL)
;; evaluates FLANG expressions by reducing them to values
(define (eval expr env)
  (cases expr
    [(Num n) (NumV n)]
    [(Add l r) (arith-op + (eval l env) (eval r env))]
    [(Sub l r) (arith-op - (eval l env) (eval r env))]
    [(Mul l r) (arith-op * (eval l env) (eval r env))]
    [(Div l r) (arith-op / (eval l env) (eval r env))]
    [(With bound-id named-expr bound-body)
    (eval bound-body
          (Extend bound-id (eval named-expr env) env))]
    [(Id name) (lookup name env)]
    [(Fun bound-id bound-body)
    (FunV bound-id bound-body env)]
    [(Call fun-expr arg-expr)
    (let ([fval (eval fun-expr env)])
      (cases fval
        [(FunV bound-id bound-body f-env)
          (eval bound-body
                (Extend bound-id (eval arg-expr env) f-env))]
        [else (error 'eval "`call' expects a function, got: ~s"
                            fval)]))]))

(: run : String -> Number)
;; evaluate a FLANG program contained in a string
(define (run str)
  (let ([result (eval (parse str) (EmptyEnv))])
    (cases result
      [(NumV n) n]
      [else (error 'run "evaluation returned a non-number: ~s"
                  result)])))

;; tests
(test (run "{call {fun {x} {+ x 1}} 4}")
      => 5)
(test (run "{with {add3 {fun {x} {+ x 3}}}
              {call add3 1}}")
      => 4)
(test (run "{with {add3 {fun {x} {+ x 3}}}
              {with {add1 {fun {x} {+ x 1}}}
                {with {x 3}
                  {call add1 {call add3 x}}}}}")
      => 7)
(test (run "{with {identity {fun {x} x}}
              {with {foo {fun {x} {+ x 1}}}
                {call {call identity foo} 123}}}")
      => 124)
(test (run "{with {x 3}
              {with {f {fun {y} {+ x y}}}
                {with {x 5}
                  {call f 4}}}}")
      => 7)
(test (run "{call {with {x 3}
                    {fun {y} {+ x y}}}
                  4}")
      => 7)
(test (run "{with {f {with {x 3} {fun {y} {+ x y}}}}
              {with {x 100}
                {call f 4}}}")
      => 7)
(test (run "{call {call {fun {x} {call x 1}}
                        {fun {x} {fun {y} {+ x y}}}}
                  123}")
      => 124)

More Closures (on both levels)Tuesday, October 9th

Racket closures (= functions) can be used in other places too, and as we have seen, they can do more than encapsulate various values — they can also hold the behavior that is expected of these values.

To demonstrate this we will deal with closures in our language. We currently use a variant that holds the three pieces of relevant information:

[FunV Symbol FLANG ENV]

We can replace this by a functional object, which will hold the three values. First, change the VAL type to hold functions for FunV values:

(define-type VAL
  [NumV Number]
  [FunV (? -> ?)])

And note that the function should somehow encapsulate the same information that was there previously, the question is how this information is going to be done, and this will determine the actual type. This information plays a role in two places in our evaluator — generating a closure in the Fun case, and using it in the Call case:

[(Fun bound-id bound-body)
(FunV bound-id bound-body env)]
[(Call fun-expr arg-expr)
(let ([fval (eval fun-expr env)])
  (cases fval
    [(FunV bound-id bound-body f-env)
      (eval bound-body                  ;***
            (Extend bound-id            ;***
                    (eval arg-expr env)  ;***
                    f-env))]            ;***
    [else (error 'eval "`call' expects a function, got: ~s"
                        fval)]))]

we can simply fold the marked functionality bit of Call into a Racket function that will be stored in a FunV object — this piece of functionality takes an argument value, extends the closure’s environment with its value and the function’s name, and continues to evaluate the function body. Folding all of this into a function gives us:

(lambda (arg-val)
  (eval bound-body (Extend bound-id arg-val env)))

where the values of bound-body, bound-id, and val are known at the time that the FunV is constructed. Doing this gives us the following code for the two cases:

[(Fun bound-id bound-body)
(FunV (lambda (arg-val)
        (eval bound-body (Extend bound-id arg-val env))))]
[(Call fun-expr arg-expr)
(let ([fval (eval fun-expr env)])
  (cases fval
    [(FunV proc) (proc (eval arg-expr env))]
    [else (error 'eval "`call' expects a function, got: ~s"
                        fval)]))]

And now the type of the function is clear:

(define-type VAL
  [NumV Number]
  [FunV (VAL -> VAL)])

And again, the rest of the code is unmodified:

#lang pl

(define-type FLANG
  [Num  Number]
  [Add  FLANG FLANG]
  [Sub  FLANG FLANG]
  [Mul  FLANG FLANG]
  [Div  FLANG FLANG]
  [Id  Symbol]
  [With Symbol FLANG FLANG]
  [Fun  Symbol FLANG]
  [Call FLANG FLANG])

(: parse-sexpr : Sexpr -> FLANG)
;; parses s-expressions into FLANGs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(cons 'with more)
    (match sexpr
      [(list 'with (list (symbol: name) named) body)
        (With name (parse-sexpr named) (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `with' syntax in ~s" sexpr)])]
    [(cons 'fun more)
    (match sexpr
      [(list 'fun (list (symbol: name)) body)
        (Fun name (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `fun' syntax in ~s" sexpr)])]
    [(list '+ lhs rhs) (Add (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '- lhs rhs) (Sub (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '* lhs rhs) (Mul (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '/ lhs rhs) (Div (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list 'call fun arg)
                      (Call (parse-sexpr fun) (parse-sexpr arg))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

(: parse : String -> FLANG)
;; parses a string containing a FLANG expression to a FLANG AST
(define (parse str)
  (parse-sexpr (string->sexpr str)))

;; Types for environments, values, and a lookup function

(define-type VAL
  [NumV Number]
  [FunV (VAL -> VAL)])

;; Define a type for functional environments
(define-type ENV = Symbol -> VAL)

(: EmptyEnv : -> ENV)
(define (EmptyEnv)
  (lambda (id) (error 'lookup "no binding for ~s" id)))

(: Extend : Symbol VAL ENV -> ENV)
;; extend a given environment cache with a new binding
(define (Extend id val rest-env)
  (lambda (name)
    (if (eq? name id)
      val
      (rest-env name))))

(: lookup : Symbol ENV -> VAL)
;; lookup a symbol in an environment, return its value or throw an
;; error if it isn't bound
(define (lookup name env)
  (env name))

(: NumV->number : VAL -> Number)
;; convert a FLANG runtime numeric value to a Racket one
(define (NumV->number val)
  (cases val
    [(NumV n) n]
    [else (error 'arith-op "expected a number, got: ~s" val)]))

(: arith-op : (Number Number -> Number) VAL VAL -> VAL)
;; gets a Racket numeric binary operator, and uses it within a NumV
;; wrapper
(define (arith-op op val1 val2)
  (NumV (op (NumV->number val1) (NumV->number val2))))

(: eval : FLANG ENV -> VAL)
;; evaluates FLANG expressions by reducing them to values
(define (eval expr env)
  (cases expr
    [(Num n) (NumV n)]
    [(Add l r) (arith-op + (eval l env) (eval r env))]
    [(Sub l r) (arith-op - (eval l env) (eval r env))]
    [(Mul l r) (arith-op * (eval l env) (eval r env))]
    [(Div l r) (arith-op / (eval l env) (eval r env))]
    [(With bound-id named-expr bound-body)
    (eval bound-body
          (Extend bound-id (eval named-expr env) env))]
    [(Id name) (lookup name env)]
    [(Fun bound-id bound-body)
    (FunV (lambda (arg-val)
            (eval bound-body (Extend bound-id arg-val env))))]
    [(Call fun-expr arg-expr)
    (let ([fval (eval fun-expr env)])
      (cases fval
        [(FunV proc) (proc (eval arg-expr env))]
        [else (error 'eval "`call' expects a function, got: ~s"
                            fval)]))]))

(: run : String -> Number)
;; evaluate a FLANG program contained in a string
(define (run str)
  (let ([result (eval (parse str) (EmptyEnv))])
    (cases result
      [(NumV n) n]
      [else (error 'run "evaluation returned a non-number: ~s"
                  result)])))

;; tests
(test (run "{call {fun {x} {+ x 1}} 4}")
      => 5)
(test (run "{with {add3 {fun {x} {+ x 3}}}
              {call add3 1}}")
      => 4)
(test (run "{with {add3 {fun {x} {+ x 3}}}
              {with {add1 {fun {x} {+ x 1}}}
                {with {x 3}
                  {call add1 {call add3 x}}}}}")
      => 7)
(test (run "{with {identity {fun {x} x}}
              {with {foo {fun {x} {+ x 1}}}
                {call {call identity foo} 123}}}")
      => 124)
(test (run "{with {x 3}
              {with {f {fun {y} {+ x y}}}
                {with {x 5}
                  {call f 4}}}}")
      => 7)
(test (run "{call {with {x 3}
                    {fun {y} {+ x y}}}
                  4}")
      => 7)
(test (run "{with {f {with {x 3} {fun {y} {+ x y}}}}
              {with {x 100}
                {call f 4}}}")
      => 7)
(test (run "{call {call {fun {x} {call x 1}}
                        {fun {x} {fun {y} {+ x y}}}}
                  123}")
      => 124)

Types of EvaluatorsTuesday, October 9th

What we did just now is implement lexical environments and closures in the language we implement using lexical environments and closures in our own language (Racket)!

This is another example of embedding a feature of the host language in the implemented language, an issue that we have already discussed.

There are many examples of this, even when the two languages involved are different. For example, if we have this bit in the C implementation of Racket:

// Disclaimer: not real Racket code
Racket_Object *eval_and( int argc, Racket_Object *argv[] )
{
  Racket_Object *tmp;
  if ( argc != 2 )
    signal_racket_error("bad number of arguments");
  else if ( racket_eval(argv[0]) != racket_false &&
            (tmp = racket_eval(argv[1])) != racket_false )
    return tmp;
  else
    return racket_false;
}

then the special semantics of evaluating a Racket and form is being inherited from C’s special treatment of &&. You can see this by the fact that if there is a bug in the C compiler, then it will propagate to the resulting Racket implementation too. A different solution is to not use && at all:

// Disclaimer: not real Racket code
Racket_Object *eval_and( int argc, Racket_Object *argv[] )
{
  Racket_Object *tmp;
  if ( argc != 2 )
    signal_racket_error("bad number of arguments");
  else if ( racket_eval(argv[0]) != racket_false )
    return racket_eval(argv[1]);
  else
    return racket_false;
}

and we can say that this is even better since it evaluates the second expression in tail position. But in this case we don’t really get that benefit, since C itself is not doing tail-call optimization as a standard feature (though some compilers do so under some circumstances).

We have seen a few different implementations of evaluators that are quite different in flavor. They suggest the following taxonomy.

While our substitution-based FLANG evaluator was close to being a syntactic evaluator, we haven’t written any purely syntactic evaluators so far: we still relied on things like Racket arithmetics etc. The most recent evaluator that we have studied, is distinctly a meta evaluator.

With a good match between the evaluated language and the implementation language, writing a meta evaluator can be very easy. With a bad match, though, it can be very hard. With a syntactic evaluator, implementing each semantic feature will be somewhat hard, but in return you don’t have to worry as much about how well the implementation and the evaluated languages match up. In particular, if there is a particularly strong mismatch between the implementation and the evaluated language, it may take less effort to write a syntactic evaluator than a meta evaluator. As an exercise, we can build upon our latest evaluator to remove the encapsulation of the evaluator’s response in the VAL type. The resulting evaluator is shown below. This is a true meta evaluator: it uses Racket closures to implement FLANG closures, Racket function application for FLANG function application, Racket numbers for FLANG numbers, and Racket arithmetic for FLANG arithmetic. In fact, ignoring some small syntactic differences between Racket and FLANG, this latest evaluator can be classified as something more specific than a meta evaluator:

(Put differently, the trivial nature of the evaluator clues us in to the deep connection between the two languages, whatever their syntactic differences may be.)

Feature EmbeddingTuesday, October 9th

We saw that the difference between lazy evaluation and eager evaluation is in the evaluation rules for with forms, function applications, etc:

eval({with {x E1} E2}) = eval(E2[eval(E1)/x])

is eager, and

eval({with {x E1} E2}) = eval(E2[E1/x])

is lazy. But is the first rule really eager? The fact is that the only thing that makes it eager is the fact that our understanding of the mathematical notation is eager — if we were to take math as lazy, then the description of the rule becomes a description of lazy evaluation.

Another way to look at this is — take the piece of code that implements this evaluation:

(: eval : FLANG -> Number)
;; evaluates FLANG expressions by reducing them to numbers
(define (eval expr)
  (cases expr
    ...
    [(With bound-id named-expr bound-body)
    (eval (subst bound-body
                  bound-id
                  (Num (eval named-expr))))]
    ...))

and the same question applies: is this really implementing eager evaluation? We know that this is indeed eager — we can simply try it and check that it is, but it is only eager because we are using an eager language for the implementation! If our own language was lazy, then the evaluator’s implementation would run lazily, which means that the above applications of the eval and the subst functions would also be lazy, making our evaluator lazy as well.

This is a general phenomena where some of the semantic features of the language we use (math in the formal description, Racket in our code) gets embedded into the language we implement.

Here’s another example — consider the code that implements arithmetics:

(: eval : FLANG -> Number)
;; evaluates FLANG expressions by reducing them to numbers
(define (eval expr)
  (cases expr
    [(Num n) n]
    [(Add l r) (+ (eval l) (eval r))]
    ...))

what if it was written like this:

FLANG eval(FLANG expr) {
  if (is_Num(expr))
    return num_of_Num(expr);
  else if (is_Add(expr))
    return eval(lhs_of_Add(expr)) + eval(rhs_of_Add(expr));
  else if ...
  ...
}

Would it still implement unlimited integers and exact fractions? That depends on the language that was used to implement it: the above syntax suggests C, C++, Java, or some other relative, which usually come with limited integers and no exact fractions. But this really depends on the language — even our own code has unlimited integers and exact rationals only because Racket has them. If we were using a language that didn’t have such features (there are such Scheme implementations), then our implemented language would absorb these (lack of) features too, and its own numbers would be limited in just the same way. (And this includes the syntax for numbers, which we embedded intentionally, like the syntax for identifiers).

The bottom line is that we should be aware of such issues, and be very careful when we talk about semantics. Even the language that we use to communicate (semi-formal logic) can mean different things.


Aside: read “Reflections on Trusting Trust” by Ken Thompson (You can skip to the “Stage II” part to get to the interesting stuff.)

(And when you’re done, look for “XcodeGhost” to see a relevant example, and don’t miss the leaked document on the wikipedia page…)


Here is yet another variation of our evaluator that is even closer to a meta-circular evaluator. It uses Racket values directly to implement values, so arithmetic operations become straightforward. Note especially how the case for function application is similar to arithmetics: a FLANG function application translates to a Racket function application. In both cases (applications and arithmetics) we don’t even check the objects since they are simple Racket objects — if our language happens to have some meaning for arithmetics with functions, or for applying numbers, then we will inherit the same semantics in our language. This means that we now specify less behavior and fall back more often on what Racket does.

We use Racket values with this type definition:

(define-type VAL = (U Number (VAL -> VAL)))

And the evaluation function can now be:

(: eval : FLANG ENV -> VAL)
;; evaluates FLANG expressions by reducing them to values
(define (eval expr env)
  (cases expr
    [(Num n) n]                ;*** return the actual number
    [(Add l r) (+ (eval l env) (eval r env))]
    [(Sub l r) (- (eval l env) (eval r env))]
    [(Mul l r) (* (eval l env) (eval r env))]
    [(Div l r) (/ (eval l env) (eval r env))]
    [(With bound-id named-expr bound-body)
    (eval bound-body
          (Extend bound-id (eval named-expr env) env))]
    [(Id name) (lookup name env)]
    [(Fun bound-id bound-body)
    (lambda ([arg-val : VAL]) ;*** return the racket function
      ;; note that this requires input type specifications since
      ;; typed racket can't guess the right one
      (eval bound-body (Extend bound-id arg-val env)))]
    [(Call fun-expr arg-expr)
    ((eval fun-expr env)      ;*** trivial like the arithmetics!
      (eval arg-expr env))]))

Note how the arithmetics implementation is simple — it’s a direct translation of the FLANG syntax to Racket operations, and since we don’t check the inputs to the Racket operations, we let Racket throw type errors for us. Note also how function application is just like the arithmetic operations: a FLANG application is directly translated to a Racket application.

However, this does not work quite as simply in Typed Racket. The whole point of typechecking is that we never run into type errors — so we cannot throw back on Racket errors since code that might produce them is forbidden! A way around this is to perform explicit checks that guarantee that Racket cannot run into type errors. We do this with the following two helpers that are defined inside eval:

  (: evalN : FLANG -> Number)
  (define (evalN e)
    (let ([n (eval e env)])
      (if (number? n)
        n
        (error 'eval "got a non-number: ~s" n))))
  (: evalF : FLANG -> (VAL -> VAL))
  (define (evalF e)
    (let ([f (eval e env)])
      (if (function? f)
        f
        (error 'eval "got a non-function: ~s" f))))

Note that Typed Racket is “smart enough” to figure out that in evalF the result of the recursive evaluation has to be either Number or (VAL -> VAL); and since the if throws out on numbers, we’re left with (VAL -> VAL) functions, not just any function.

#lang pl

(define-type FLANG
  [Num  Number]
  [Add  FLANG FLANG]
  [Sub  FLANG FLANG]
  [Mul  FLANG FLANG]
  [Div  FLANG FLANG]
  [Id  Symbol]
  [With Symbol FLANG FLANG]
  [Fun  Symbol FLANG]
  [Call FLANG FLANG])

(: parse-sexpr : Sexpr -> FLANG)
;; parses s-expressions into FLANGs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(cons 'with more)
    (match sexpr
      [(list 'with (list (symbol: name) named) body)
        (With name (parse-sexpr named) (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `with' syntax in ~s" sexpr)])]
    [(cons 'fun more)
    (match sexpr
      [(list 'fun (list (symbol: name)) body)
        (Fun name (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `fun' syntax in ~s" sexpr)])]
    [(list '+ lhs rhs) (Add (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '- lhs rhs) (Sub (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '* lhs rhs) (Mul (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '/ lhs rhs) (Div (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list 'call fun arg)
                      (Call (parse-sexpr fun) (parse-sexpr arg))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

(: parse : String -> FLANG)
;; parses a string containing a FLANG expression to a FLANG AST
(define (parse str)
  (parse-sexpr (string->sexpr str)))

;; Types for environments, values, and a lookup function

;; Values are plain Racket values, no new VAL wrapper;
;; (but note that this is a recursive definition)
(define-type VAL = (U Number (VAL -> VAL)))

;; Define a type for functional environments
(define-type ENV = (Symbol -> VAL))

(: EmptyEnv : -> ENV)
(define (EmptyEnv)
  (lambda (id) (error 'lookup "no binding for ~s" id)))

(: Extend : Symbol VAL ENV -> ENV)
;; extend a given environment cache with a new binding
(define (Extend id val rest-env)
  (lambda (name)
    (if (eq? name id)
      val
      (rest-env name))))

(: lookup : Symbol ENV -> VAL)
;; lookup a symbol in an environment, return its value or throw an
;; error if it isn't bound
(define (lookup name env)
  (env name))

(: eval : FLANG ENV -> VAL)
;; evaluates FLANG expressions by reducing them to values
(define (eval expr env)
  (: evalN : FLANG -> Number)
  (define (evalN e)
    (let ([n (eval e env)])
      (if (number? n)
        n
        (error 'eval "got a non-number: ~s" n))))
  (: evalF : FLANG -> (VAL -> VAL))
  (define (evalF e)
    (let ([f (eval e env)])
      (if (function? f)
        f
        (error 'eval "got a non-function: ~s" f))))
  (cases expr
    [(Num n) n]
    [(Add l r) (+ (evalN l) (evalN r))]
    [(Sub l r) (- (evalN l) (evalN r))]
    [(Mul l r) (* (evalN l) (evalN r))]
    [(Div l r) (/ (evalN l) (evalN r))]
    [(With bound-id named-expr bound-body)
    (eval bound-body
          (Extend bound-id (eval named-expr env) env))]
    [(Id name) (lookup name env)]
    [(Fun bound-id bound-body)
    (lambda ([arg-val : VAL])
      (eval bound-body (Extend bound-id arg-val env)))]
    [(Call fun-expr arg-expr)
    ((evalF fun-expr)
      (eval arg-expr env))]))

(: run : String -> VAL) ; no need to convert VALs to numbers
;; evaluate a FLANG program contained in a string
(define (run str)
  (eval (parse str) (EmptyEnv)))

;; tests
(test (run "{call {fun {x} {+ x 1}} 4}")
      => 5)
(test (run "{with {add3 {fun {x} {+ x 3}}}
              {call add3 1}}")
      => 4)
(test (run "{with {add3 {fun {x} {+ x 3}}}
              {with {add1 {fun {x} {+ x 1}}}
                {with {x 3}
                  {call add1 {call add3 x}}}}}")
      => 7)
(test (run "{with {identity {fun {x} x}}
              {with {foo {fun {x} {+ x 1}}}
                {call {call identity foo} 123}}}")
      => 124)
(test (run "{with {x 3}
              {with {f {fun {y} {+ x y}}}
                {with {x 5}
                  {call f 4}}}}")
      => 7)
(test (run "{call {with {x 3}
                    {fun {y} {+ x y}}}
                  4}")
      => 7)
(test (run "{with {f {with {x 3} {fun {y} {+ x y}}}}
              {with {x 100}
                {call f 4}}}")
      => 7)
(test (run "{call {call {fun {x} {call x 1}}
                        {fun {x} {fun {y} {+ x y}}}}
                  123}")
      => 124)

Recursion, Recursion, RecursionTuesday, October 16th

PLAI §9

There is one major feature that is still missing from our language: we have no way to perform recursion (therefore no kind of loops). So far, we could only use recursion when we had names. In FLANG, the only way we can have names is through with which not good enough for recursion.

To discuss the issue of recursion, we switch to a “broken” version of (untyped) Racket — one where a define has a different scoping rules: the scope of the defined name does not cover the defined expression. Specifically, in this language, this doesn’t work:

#lang pl broken
(define (fact n)
  (if (zero? n) 1 (* n (fact (- n 1)))))
(fact 5)

In our language, this translation would also not work (assuming we have if etc):

{with {fact {fun {n}
              {if {= n 0} 1 {* n {call fact {- n 1}}}}}}
  {call fact 5}}

And similarly, in plain Racket this won’t work if let is the only tool you use to create bindings:

(let ([fact (lambda (n)
              (if (zero? n) 1 (* n (fact (- n 1)))))])
  (fact 5))

In the broken-scope language, the define form is more similar to a mathematical definition. For example, when we write:

(define (F x) x)
(define (G y) (F y))
(G F)

it is actually shorthand for

(define F (lambda (x) x))
(define G (lambda (y) (F y)))
(G F)

we can then replace defined names with their definitions:

(define F (lambda (x) x))
(define G (lambda (y) (F y)))
((lambda (y) (F y)) (lambda (x) x))

and this can go on, until we get to the actual code that we wrote:

((lambda (y) ((lambda (x) x) y)) (lambda (x) x))

This means that the above fact definition is similar to writing:

fact := (lambda (n)
          (if (zero? n) 1 (* n (fact (- n 1)))))
(fact 5)

which is not a well-formed definition — it is meaningless (this is a formal use of the word “meaningless”). What we’d really want, is to take the equation (using = instead of :=)

fact = (lambda (n)
        (if (zero? n) 1 (* n (fact (- n 1)))))

and find a solution which will be a value for fact that makes this true.

If you look at the Racket evaluation rules handout on the web page, you will see that this problem is related to the way that we introduced the Racket define: there is a hand-wavy explanation that talks about knowing things.

The big question is: can we define recursive functions without Racket’s magical define form?

Note: This question is a little different than the question of implementing recursion in our language — in the Racket case we have no control over the implementation of the language. As it will eventually turn out, implementing recursion in our own language will be quite easy when we use mutation in a specific way. So the question that we’re now facing can be phrased as either “can we get recursion in Racket without Racket’s magical definition forms?” or “can we get recursion in our interpreter without mutation?”.

Recursion without the MagicTuesday, October 16th

PLAI §22.4 (we go much deeper)

Note: This explanation is similar to the one you can find in “The Why of Y”, by Richard Gabriel.

To implement recursion without the define magic, we first make an observation: this problem does not come up in a dynamically-scoped language. Consider the let-version of the problem:

#lang pl dynamic
(let ([fact (lambda (n)
              (if (zero? n) 1 (* n (fact (- n 1)))))])
  (fact 5))

This works fine — because by the time we get to evaluate the body of the function, fact is already bound to itself in the current dynamic scope. (This is another reason why dynamic scope is perceived as a convenient approach in new languages.)

Regardless, the problem that we have with lexical scope is still there, but the way things work in a dynamic scope suggest a solution that we can use now. Just like in the dynamic scope case, when fact is called, it does have a value — the only problem is that this value is inaccessible in the lexical scope of its body.

Instead of trying to get the value in via lexical scope, we can imitate what happens in the dynamically scoped language by passing the fact value to itself so it can call itself (going back to the original code in the broken-scope language):

(define (fact self n)  ;***
  (if (zero? n) 1 (* n (self (- n 1)))))
(fact fact 5)          ;***

except that now the recursive call should still send itself along:

(define (fact self n)
  (if (zero? n) 1 (* n (self self (- n 1))))) ;***
(fact fact 5)

The problem is that this required rewriting calls to fact — both outside and recursive calls inside. To make this an acceptable solution, calls from both places should not change. Eventually, we should be able to get a working fact definition that uses just

(lambda (n) (if (zero? n) 1 (* n (fact (- n 1)))))

The first step in resolving this problem is to curry the fact definition.

(define (fact self)                  ;***
  (lambda (n)                        ;***
    (if (zero? n)
      1
      (* n ((self self) (- n 1)))))) ;***
((fact fact) 5)                      ;***

Now fact is no longer our factorial function — it’s a function that constructs it. So call it make-fact, and bind fact to the actual factorial function.

(define (make-fact self)            ;***
  (lambda (n)
    (if (zero? n) 1 (* n ((self self) (- n 1))))))
(define fact (make-fact make-fact))  ;***
(fact 5)                            ;***

We can try to do the same thing in the body of the factorial function: instead of calling (self self), just bind fact to it:

(define (make-fact self)
  (lambda (n)
    (let ([fact (self self)])      ;***
      (if (zero? n)
        1
        (* n (fact (- n 1)))))))    ;***
(define fact (make-fact make-fact))
(fact 5)

This works fine, but if we consider our original goal, we need to get that local fact binding outside of the (lambda (n) ...) — so we’re left with a definition that uses the factorial expression as is. So, swap the two lines:

(define (make-fact self)
  (let ([fact (self self)])  ;***
    (lambda (n)              ;***
      (if (zero? n) 1 (* n (fact (- n 1)))))))
(define fact (make-fact make-fact))
(fact 5)

But the problem is that this gets us into an infinite loop because we’re trying to evaluate (self self) too early. In fact, if we ignore the body of the let and other details, we basically do this:

(define (make-fact self) (self self)) (make-fact make-fact)
--reduce-sugar-->
(define make-fact (lambda (self) (self self))) (make-fact make-fact)
--replace-definition-->
((lambda (self) (self self)) (lambda (self) (self self)))
--rename-identifiers-->
((lambda (x) (x x)) (lambda (x) (x x)))

And this expression has an interesting property: it reduces to itself, so evaluating it gets stuck in an infinite loop.

So how do we solve this? Well, we know that (self self) should be the same value that is the factorial function itself — so it must be a one-argument function. If it’s such a function, we can use a value that is equivalent, except that it will not get evaluated until it is needed, when the function is called. The trick here is the observation that (lambda (n) (add1 n)) is really the same function as add1, except that the add1 part doesn’t get evaluated until the function is called. Applying this trick to our code produces a version that does not get stuck in the same infinite loop:

(define (make-fact self)
  (let ([fact (lambda (n) ((self self) n))]) ;***
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1)))))))
(define fact (make-fact make-fact))
(fact 5)

Continuing from here — we know that

(let ([x v]) e)  is the same as  ((lambda (x) e) v)

(remember how we derived fun from a with), so we can turn that let into the equivalent function application form:

(define (make-fact self)
  ((lambda (fact)                    ;***
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1))))))
  (lambda (n) ((self self) n))))    ;***
(define fact (make-fact make-fact))
(fact 5)

And note now that the (lambda (fact) …) expression is everything that we need for a recursive definition of fact — it has the proper factorial body with a plain recursive call. It’s almost like the usual value that we’d want to define fact as, except that we still have to abstract on the recursive value itself. So lets move this code into a separate definition for fact-core:

(define fact-core                  ;***
  (lambda (fact)
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1)))))))
(define (make-fact self)
  (fact-core                        ;***
  (lambda (n) ((self self) n))))
(define fact (make-fact make-fact))
(fact 5)

We can now proceed by moving the (make-fact make-fact) self application into its own function which is what creates the real factorial:

(define fact-core
  (lambda (fact)
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1)))))))
(define (make-fact self)
  (fact-core
  (lambda (n) ((self self) n))))
(define (make-real-fact) (make-fact make-fact)) ;***
(define fact (make-real-fact))                  ;***
(fact 5)

Rewrite the make-fact definition using an explicit lambda:

(define fact-core
  (lambda (fact)
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1)))))))
(define make-fact                    ;***
  (lambda (self)                      ;***
    (fact-core
    (lambda (n) ((self self) n)))))
(define (make-real-fact) (make-fact make-fact))
(define fact (make-real-fact))
(fact 5)

and fold the functionality of make-fact and make-real-fact into a single make-fact function by just using the value of make-fact explicitly instead of through a definition:

(define fact-core
  (lambda (fact)
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1)))))))
(define (make-real-fact)
  (let ([make (lambda (self)                      ;***
                (fact-core                        ;***
                (lambda (n) ((self self) n))))]) ;***
    (make make)))
(define fact (make-real-fact))
(fact 5)

We can now observe that make-real-fact has nothing that is specific to factorial — we can make it take a “core function” as an argument:

(define fact-core
  (lambda (fact)
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1)))))))
(define (make-real-fact core)                    ;***
  (let ([make (lambda (self)
                (core                            ;***
                (lambda (n) ((self self) n))))])
    (make make)))
(define fact (make-real-fact fact-core))          ;***
(fact 5)

and call it make-recursive:

(define fact-core
  (lambda (fact)
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1)))))))
(define (make-recursive core)            ;***
  (let ([make (lambda (self)
                (core
                (lambda (n) ((self self) n))))])
    (make make)))
(define fact (make-recursive fact-core))  ;***
(fact 5)

We’re almost done now — there’s no real need for a separate fact-core definition, just use the value for the definition of fact:

(define (make-recursive core)
  (let ([make (lambda (self)
                (core
                (lambda (n) ((self self) n))))])
    (make make)))
(define fact
  (make-recursive
  (lambda (fact)                                          ;***
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1)))))))) ;***
(fact 5)

turn the let into a function form:

(define (make-recursive core)
  ((lambda (make) (make make))              ;***
  (lambda (self)                          ;***
    (core (lambda (n) ((self self) n)))))) ;***
(define fact
  (make-recursive
  (lambda (fact)
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1))))))))
(fact 5)

do some renamings to make things simpler — make and self turn to x, and core to f:

(define (make-recursive f)                  ;***
  ((lambda (x) (x x))                        ;***
  (lambda (x) (f (lambda (n) ((x x) n)))))) ;***
(define fact
  (make-recursive
  (lambda (fact)
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1))))))))
(fact 5)

or we can manually expand that first (lambda (x) (x x)) application to make the symmetry more obvious (not really surprising because it started with a let whose purpose was to do a self-application):

(define (make-recursive f)
  ((lambda (x) (f (lambda (n) ((x x) n))))  ;***
  (lambda (x) (f (lambda (n) ((x x) n)))))) ;***
(define fact
  (make-recursive
  (lambda (fact)
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1))))))))
(fact 5)

And we finally got what we were looking for: a general way to define any recursive function without any magical define tricks. This also work for other recursive functions:

#lang pl broken
(define (make-recursive f)
  ((lambda (x) (f (lambda (n) ((x x) n))))
  (lambda (x) (f (lambda (n) ((x x) n))))))
(define fact
  (make-recursive
  (lambda (fact)
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1))))))))
(fact 5)
(define fib
  (make-recursive
  (lambda (fib)
    (lambda (n) (if (<= n 1) n (+ (fib (- n 1)) (fib (- n 2))))))))
(fib 8)
(define length
  (make-recursive
  (lambda (length)
    (lambda (l) (if (null? l) 0 (+ (length (rest l)) 1))))))
(length '(x y z))

A convenient tool that people often use on paper is to perform a kind of a syntactic abstraction: “assume that whenever I write (twice foo) I really meant to write (foo foo)”. This can often be done as plain abstractions (that is, using functions), but in some cases — for example, if we want to abstract over definitions — we just want such a rewrite rule. (More on this towards the end of the course.) The broken-scope language does provide such a tool — rewrite extends the language with a rewrite rule. Using this, and our make-recursive, we can make up a recursive definition form:

(rewrite (define/rec (f x) E)
      => (define f (make-recursive (lambda (f) (lambda (x) E)))))

In other words, we’ve created our own “magical definition” form. The above code can now be written in almost the same way it is written in plain Racket:

#lang pl broken
(define (make-recursive f)
  ((lambda (x) (f (lambda (n) ((x x) n))))
  (lambda (x) (f (lambda (n) ((x x) n))))))
(rewrite (define/rec (f x) E)
      => (define f (make-recursive (lambda (f) (lambda (x) E)))))
;; examples
(define/rec (fact n) (if (zero? n) 1 (* n (fact (- n 1)))))
(fact 5)
(define/rec (fib n) (if (<= n 1) n (+ (fib (- n 1)) (fib (- n 2)))))
(fib 8)
(define/rec (length l) (if (null? l) 0 (+ (length (rest l)) 1)))
(length '(x y z))

Finally, note that make-recursive is limited to 1-argument functions only because of the protection from eager evaluation. In any case, it can be used in any way you want, for example,

(make-recursive (lambda (f) (lambda (x) f)))

is a function that returns itself rather than calling itself. Using the rewrite rule, this would be:

(define/rec (f x) f)

which is the same as:

(define (f x) f)

in plain Racket.

The Core of make-recursiveTuesday, October 16th

As in Racket, being able to express recursive functions is a fundamental property of the language. It means that we can have loops in our language, and that’s the essence of making a language powerful enough to be TM-equivalent — able to express undecidable problems, where we don’t know whether there is an answer or not.

The core of what makes this possible is the expression that we have seen in our derivation:

((lambda (x) (x x)) (lambda (x) (x x)))

which reduces to itself, and therefore has no value: trying to evaluate it gets stuck in an infinite loop. (This expression is often called “Omega”.)

This is the key for creating a loop — we use it to make recursion possible. Looking at our final make-recursive definition and ignoring for a moment the “protection” that we need against being stuck prematurely in an infinite loop:

(define (make-recursive f)
  ((lambda (x) (x x)) (lambda (x) (f (x x)))))

we can see that this is almost the same as the Omega expression — the only difference is that application of f. Indeed, this expression (the result of (make-recursive F) for some F) reduces in a similar way to Omega:

((lambda (x) (x x)) (lambda (x) (F (x x))))
((lambda (x) (F (x x))) (lambda (x) (F (x x))))
(F ((lambda (x) (F (x x))) (lambda (x) (F (x x)))))
(F (F ((lambda (x) (F (x x))) (lambda (x) (F (x x))))))
(F (F (F ((lambda (x) (F (x x))) (lambda (x) (F (x x)))))))
...

which means that the actual value of this expression is:

(F (F (F ...forever...)))

This definition would be sufficient if we had a lazy language, but to get things working in a strict one we need to bring back the protection. This makes things a little different — if we use (protect f) to be a shorthand for the protection trick,

(rewrite (protect f) => (lambda (x) (f x)))

then we have:

(define (make-recursive f)
  ((lambda (x) (x x)) (lambda (x) (f (protect (x x))))))

which makes the (make-recursive F) evaluation reduce to

(F (protect (F (protect (F (protect (...forever...)))))))

and this is still the same result (as long as F is a single-argument function).

(Note that protect cannot be implemented as a plain function!)

Denotational Explanation of RecursionTuesday, October 16th

Note: This explanation is similar to the one you can find in “The Little Schemer” called “(Y Y) Works!”, by Dan Friedman and Matthias Felleisen.

The explanation that we have now for how to derive the make-recursive definition is fine — after all, we did manage to get it working. But this explanation was done from a kind of an operational point of view: we knew a certain trick that can make things work and we pushed things around until we got it working like we wanted. Instead of doing this, we can re-approach the problem from a more declarative point of view.

So, start again from the same broken code that we had (using the broken-scope language):

(define fact
  (lambda (n) (if (zero? n) 1 (* n (fact (- n 1))))))

This is as broken as it was when we started: the occurrence of fact in the body of the function is free, which means that this code is meaningless. To avoid the compilation error that we get when we run this code, we can substitute anything for that fact — it’s even better to use a replacement that will lead to a runtime error:

(define fact
  (lambda (n) (if (zero? n) 1 (* n (777 (- n 1)))))) ;***

This function will not work in a similar way to the original one — but there is one case where it does work: when the input value is 0 (since then we do not reach the bogus application). We note this by calling this function fact0:

(define fact0                ;***
  (lambda (n) (if (zero? n) 1 (* n (777 (- n 1))))))

Now that we have this function defined, we can use it to write fact1 which is the factorial function for arguments of 0 or 1:

(define fact0
  (lambda (n) (if (zero? n) 1 (* n (777 (- n 1))))))
(define fact1
  (lambda (n) (if (zero? n) 1 (* n (fact0 (- n 1))))))

And remember that this is actually just shorthand for:

(define fact1
  (lambda (n)
    (if (zero? n)
      1
      (* n ((lambda (n)
              (if (zero? n)
                1
                (* n (777 (- n 1)))))
            (- n 1))))))

We can continue in this way and write fact2 that will work for n<=2:

(define fact2
  (lambda (n) (if (zero? n) 1 (* n (fact1 (- n 1))))))

or, in full form:

(define fact2
  (lambda (n)
    (if (zero? n)
      1
      (* n ((lambda (n)
              (if (zero? n)
                1
                (* n ((lambda (n)
                        (if (zero? n)
                          1
                          (* n (777 (- n 1)))))
                      (- n 1)))))
            (- n 1))))))

If we continue this way, we will get the true factorial function, but the problem is that to handle any possible integer argument, it will have to be an infinite definition! Here is what it is supposed to look like:

(define fact0 (lambda (n) (if (zero? n) 1 (* n (777 (- n 1))))))
(define fact1 (lambda (n) (if (zero? n) 1 (* n (fact0 (- n 1))))))
(define fact2 (lambda (n) (if (zero? n) 1 (* n (fact1 (- n 1))))))
(define fact3 (lambda (n) (if (zero? n) 1 (* n (fact2 (- n 1))))))
...

The true factorial function is fact-infinity, with an infinite size. So, we’re back at the original problem…

To help make things more concise, we can observe the repeated pattern in the above, and extract a function that abstracts this pattern. This function is the same as the fact-core that we have seen previously:

(define fact-core
  (lambda (fact)
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1)))))))
(define fact0 (fact-core 777))
(define fact1 (fact-core fact0))
(define fact2 (fact-core fact1))
(define fact3 (fact-core fact2))
...

which is actually:

(define fact-core
  (lambda (fact)
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1)))))))
(define fact0 (fact-core 777))
(define fact1 (fact-core (fact-core 777)))
(define fact2 (fact-core (fact-core (fact-core 777))))
...
(define fact
  (fact-core (fact-core (fact-core (... (fact-core 777) ...)))))

Do this a little differently — rewrite fact0 as:

(define fact0
  ((lambda (mk) (mk 777))
  fact-core))

Similarly, fact1 is written as:

(define fact1
  ((lambda (mk) (mk (mk 777)))
  fact-core))

and so on, until the real factorial, which is still infinite at this stage:

(define fact
  ((lambda (mk) (mk (mk (... (mk 777) ...))))
  fact-core))

Now, look at that (lambda (mk) ...) — it is an infinite expression, but for every actual application of the resulting factorial function we only need a finite number of mk applications. We can guess how many, and as soon as we hit an application of 777 we know that our guess is too small. So instead of 777, we can try to use the maker function to create and use the next.

To make things more explicit, here is the expression that is our fact0, without the definition form:

((lambda (mk) (mk 777))
fact-core)

This function has a very low guess — it works for 0, but with 1 it will run into the 777 application. At this point, we want to somehow invoke mk again to get the next level — and since 777 does get applied, we can just replace it with mk:

((lambda (mk) (mk mk))
fact-core)

The resulting function works just the same for an input of 0 because it does not attempt a recursive call — but if we give it 1, then instead of running into the error of applying 777:

(* n (777 (- n 1)))

we get to apply fact-core there:

(* n (fact-core (- n 1)))

and this is still wrong, because fact-core expects a function as an input. To see what happens more clearly, write fact-core explicitly:

((lambda (mk) (mk mk))
(lambda (fact)
  (lambda (n) (if (zero? n) 1 (* n (fact (- n 1)))))))

The problem is in what we’re going to pass into fact-core — its fact argument will not be the factorial function, but the mk function constructor. Renaming the fact argument as mk will make this more obvious (but not change the meaning):

((lambda (mk) (mk mk))
(lambda (mk)
  (lambda (n) (if (zero? n) 1 (* n (mk (- n 1)))))))

It should now be obvious that this application of mk will not work, instead, we need to apply it on some function and then apply the result on (- n 1). To get what we had before, we can use 777 as a bogus function:

((lambda (mk) (mk mk))
(lambda (mk)
  (lambda (n) (if (zero? n) 1 (* n ((mk 777) (- n 1)))))))

This will allow one recursive call — so the definition works for both inputs of 0 and 1 — but not more. But that 777 is used as a maker function now, so instead, we can just use mk itself again:

((lambda (mk) (mk mk))
(lambda (mk)
  (lambda (n) (if (zero? n) 1 (* n ((mk mk) (- n 1)))))))

And this is a working version of the real factorial function, so make it into a (non-magical) definition:

(define fact
  ((lambda (mk) (mk mk))
  (lambda (mk)
    (lambda (n) (if (zero? n) 1 (* n ((mk mk) (- n 1))))))))

But we’re not done — we “broke” into the factorial code to insert that (mk mk) application — that’s why we dragged in the actual value of fact-core. We now need to fix this. The expression on that last line

(lambda (n) (if (zero? n) 1 (* n ((mk mk) (- n 1)))))

is close enough — it is (fact-core (mk mk)). So we can now try to rewrite our fact as:

(define fact-core
  (lambda (fact)
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1)))))))
(define fact
  ((lambda (mk) (mk mk))
  (lambda (mk) (fact-core (mk mk)))))

… and would fail in a familiar way! If it’s not familiar enough, just rename all those mks as xs:

(define fact-core
  (lambda (fact)
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1)))))))
(define fact
  ((lambda (x) (x x))
  (lambda (x) (fact-core (x x)))))

We’ve run into the eagerness of our language again, as we did before. The solution is the same — the (x x) is the factorial function, so protect it as we did before, and we have a working version:

(define fact-core
  (lambda (fact)
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1)))))))
(define fact
  ((lambda (x) (x x))
  (lambda (x) (fact-core (lambda (n) ((x x) n))))))

The rest should not be surprising now… Abstract the recursive making bit in a new make-recursive function:

(define fact-core
  (lambda (fact)
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1)))))))
(define (make-recursive f)
  ((lambda (x) (x x))
  (lambda (x) (f (lambda (n) ((x x) n))))))
(define fact (make-recursive fact-core))

and now we can do the first reduction inside make-recursive and write the fact-core expression explicitly:

#lang pl broken
(define (make-recursive f)
  ((lambda (x) (f (lambda (n) ((x x) n))))
  (lambda (x) (f (lambda (n) ((x x) n))))))
(define fact
  (make-recursive
  (lambda (fact)
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1))))))))

and this is the same code we had before.

The Y CombinatorTuesday, October 16th

Our make-recursive function is usually called the fixpoint operator or the Y combinator.

It looks really simple when using the lazy version (remember: our version is the eager one):

(define Y
  (lambda (f)
    ((lambda (x) (f (x x)))
    (lambda (x) (f (x x))))))

Note that if we do allow a recursive definition for Y itself, then the definition can follow the definition that we’ve seen:

(define (Y f) (f (Y f)))

And this all comes from the loop generated by:

((lambda (x) (x x)) (lambda (x) (x x)))

This expression, which is also called Omega (the (lambda (x) (x x)) part by itself is usually called omega and then (omega omega) is Omega), is also the idea behind many deep mathematical facts. As an example for what it does, follow the next rule:

I will say the next sentence twice:
  "I will say the next sentence twice".

(Note the usage of colon for the first and quotes for the second — what is the equivalent of that in the lambda expression?)

By itself, this just gets you stuck in an infinite loop, as Omega does, and the Y combinator adds F to that to get an infinite chain of applications — which is similar to:

I will say the next sentence twice:
  "I will hop on one foot and then say the next sentence twice".

The main property of YTuesday, October 16th

fact-core is a function that given any limited factorial, will generate a factorial that is good for one more integer input. Start with 777, which is a factorial that is good for nothing (because it’s not a function), and you can get fact0 as

fact0 == (fact-core 777)

and that’s a good factorial function only for an input of 0. Use that with fact-core again, and you get

fact1 == (fact-core fact0) == (fact-core (fact-core 777))

which is the factorial function when you only look at input values of 0 or 1. In a similar way

fact2 == (fact-core fact1)

is good for 02 — and we can continue as much as we want, except that we need to have an infinite number of applications — in the general case, we have:

fact-n == (fact-core (fact-core (fact-core ... 777)))

which is good for 0n. The real factorial would be the result of running fact-core on itself infinitely, it is fact-infinity. In other words (here fact is the real factorial):

fact = fact-infinity == (fact-core (fact-core ...infinitely...))

but note that since this is really infinity, then

fact = (fact-core (fact-core ...infinitely...))
    = (fact-core fact)

so we get an equation:

fact = (fact-core fact)

and a solution for this is going to be the real factorial. The solution is the fixed-point of the fact-core function, in the same sense that 0 is the fixed point of the sin function because

0 = (sin 0)

And the Y combinator does just that — it has this property:

(make-recursive f) = (f (make-recursive f))

or, using the more common name:

(Y f) = (f (Y f))

This property encapsulates the real magical power of Y. You can see how it works: since (Y f) = (f (Y f)), we can add an f application to both sides, giving us (f (Y f)) = (f (f (Y f))), so we get:

(Y f) = (f (Y f)) = (f (f (Y f))) = (f (f (f (Y f)))) = ...
      = (f (f (f ...)))

and we can conclude that

(Y fact-core) = (fact-core (fact-core ...infinitely...))
              = fact

Yet another explanation for YTuesday, October 16th

Here’s another explanation of how the Y combinator works. Remember that our fact-core function was actually a function that generates a factorial function based on some input, which is supposed to be the factorial function:

(define fact-core
  (lambda (fact)
    (lambda (n) (if (zero? n) 1 (* n (fact (- n 1)))))))

As we’ve seen, you can apply this function on a version of factorial that is good for inputs up to some n, and the result will be a factorial that is good for those values up to n+1. The question is what is the fixpoint of fact-core? And the answer is that if it maps factₙ factorial to factₙ₊₁, then the input will be equal to the output on the infinitieth fact, which is that actual factorial. Since Y is a fixpoint combinator, it gives us exactly that answer:

(define the-real-factorial (Y fact-core))

Typing the Y CombinatorTuesday, October 16th

Typing the Y combinator is a tricky issue. For example, in standard ML you must write a new type definition to do this:

datatype 'a t = T of 'a t -> 'a
val y = fn f => (fn (T x) => (f (fn a => x (T x) a)))
                  (T (fn (T x) => (f (fn a => x (T x) a))))

Can you find a pattern in the places where T is used? — Roughly speaking, that type definition is

;; `t' is the type name, `T' is the constructor (aka the variant)
(define-type (RecType a)  ; we don't really have polymorphic types
  [T ((RecType a) -> a)])

First note that the two fn a => ... parts are the same as our protection, so ignoring that we get:

val y = fn f => (fn (T x) => (f (x (T x))))
                  (T (fn (T x) => (f (x (T x)))))

if you now replace T with Quote, things make more sense:

val y = fn f => (fn (Quote x) => (f (x (Quote x))))
                  (Quote (fn (Quote x) => (f (x (Quote x)))))

and with our syntax, this would be:

(define (Y f)
  ((lambda (qx)
    (cases qx
      [(Quote x) (f (x (Quote x)))]))
  (Quote
    (lambda (qx)
      (cases qx
        [(Quote x) (f (x (Quote x)))])))))

it’s not really quotation — but the analogy should help: it uses Quote to distinguish functions as values that are applied (the xs) from functions that are passed as arguments.

In OCaml, this looks a little different:

# type 'a t = T of ('a t -> 'a) ;;
type 'a t = T of ('a t -> 'a)
# let y f = (fun (T x) -> x (T x))
            (T (fun (T x) -> fun z -> f (x (T x)) z)) ;;
val y : (('a -> 'b) -> 'a -> 'b) -> 'a -> 'b = <fun>
# let fact = y (fun fact n -> if n<1 then 1 else n* fact(n-1)) ;;
val fact : int -> int = <fun>
# fact 5 ;;
- : int = 120

but OCaml has also a -rectypes command line argument, which will make it infer the type by itself:

# let y f = (fun x -> x x) (fun x -> fun z -> f (x x) z) ;;
val y : (('a -> 'b) -> 'a -> 'b) -> 'a -> 'b = <fun>
# let fact = y (fun fact n -> if n<1 then 1 else n* fact(n-1)) ;;
val fact : int -> int = <fun>
# fact 5 ;;
- : int = 120

It is also possible to write this expression in Typed Racket, but we will need to write a proper type definition. First of all, the type of Y should be straightforward: it is a fixpoint operation, so it takes a T -> T function and produces its fixpoint. The fixpoint itself is some T (such that applying the function on it results in itself). So this gives us:

(: make-recursive : (T -> T) -> T)

However, in our case make-recursive computes a functional fixpoint, for unary S -> T functions, so we should narrow down the type

(: make-recursive : ((S -> T) -> (S -> T)) -> (S -> T))

Now, in the body of make-recursive we need to add a type for the x argument which is behaving in a weird way: it is used both as a function and as its own argument. (Remember — I will say the next sentence twice: “I will say the next sentence twice”.) We need a recursive type definition for that:

(define-type (Tau S T) = (Rec this (this -> (S -> T))))

This type is tailored for our use of x: given a type T, x is a function that will consume itself (hence the Rec) and spit out the value that the f argument consumes — an S -> T function.

The resulting full version of the code:

(: make-recursive : (All (S T) ((S -> T) -> (S -> T)) -> (S -> T)))
(define-type (Tau S T) = (Rec this (this -> (S -> T))))
(define (make-recursive f)
  ((lambda ([x : (Tau S T)]) (f (lambda (z) ((x x) z))))
  (lambda ([x : (Tau S T)]) (f (lambda (z) ((x x) z))))))

(: fact : Number -> Number)
(define fact (make-recursive
              (lambda ([fact : (Number -> Number)])
                (lambda ([n : Number])
                  (if (zero? n)
                    1
                    (* n (fact (- n 1))))))))

(fact 5)

Lambda Calculus — SchlacTuesday, October 16th

PLAI §22 (we do much more)

We know that many constructs that are usually thought of as primitives are not really needed — we can implement them ourselves given enough tools. The question is how far can we go?

The answer: as far as we want. For example:

(define foo((lambda(f)((lambda(x)(x x))(lambda(x)(f(x x)))))(lambda(
f)(lambda(x)(((x(lambda(x)(lambda(x y)y))(lambda(x y)x))(x(lambda(x)
(lambda(x y)y))(lambda(x y)x))(((x(lambda (p)(lambda(s)(s(p(lambda(x
y)y))(lambda(f x)(f((p(lambda(x y)y))f x))))))(lambda(s) (s(lambda(f
x)x)(lambda(f x)x))))(lambda(x y)x))(lambda(x)(lambda(x y)y))(lambda
(x y)x)))(lambda(f x)(f x))((f((x(lambda(p)(lambda(s)(s(p(lambda(x y
)y))(lambda(f x)(f((p(lambda(x y)y))f x))))))(lambda(y s)(s(lambda(f
x)x)(lambda(f x)x))))(lambda(x y)x)))(lambda(n)(lambda(f x)(f(n f x)
)))(f((((x(lambda(p)(lambda(s)(s(p (lambda(x y)y))(lambda(f x)(f((p(
lambda(x y)y))f x))))))(lambda(s)(s(lambda(f x) x)(lambda(f x)x))))(
lambda(x y)x))(lambda(p)(lambda(s)(s(p(lambda(x y)y))(lambda(f x)(f(
(p(lambda(x y)y))f x))))))(lambda(s)(s(lambda(f x)x)(lambda(f x)x)))
)(lambda(x y)x)))))))))

We begin with a very minimal language, which is based on the Lambda Calculus. In this language we get a very minimal set of constructs and values.

In DrRacket, this we will use the Schlac language level (stands for “SchemeRacket as Lambda Calculus”). This language has a Racket-like syntax, but don’t be confused — it is very different from Racket. The only constructs that are available in this language are: lambda expressions of at least one argument, function application (again, at least one argument), and simple definition forms which are similar to the ones in the “Broken define” language — definitions are used as shorthand, and cannot be used for recursive function definition. They’re also only allowed at the toplevel — no local helpers, and a definition is not an expression that can appear anywhere. The BNF is therefore:

<SCHLAC>      ::= <SCHLAC-TOP> ...

<SCHLAC-TOP>  ::= <SCHLAC-EXPR>
                | (define <id> <SCHLAC-EXPR>)

<SCHLAC-EXPR> ::= <id>
                | (lambda (<id> <id> ...) <SCHLAC-EXPR>)
                | (<SCHLAC-EXPR> <SCHLAC-EXPR> <SCHLAC-EXPR> ...)

Since this language has no primitive values (other than functions), Racket numbers and booleans are also considered identifiers, and have no built-in value that come with the language. In addition, all functions and function calls are curried, so

(lambda (x y z) (z y x))

is actually shorthand for

(lambda (x) (lambda (y) (lambda (z) ((z y) x))))

The rules for evaluation are simple, there is one very important rule for evaluation which is called “beta reduction”:

((lambda (x) E1) E2) --> E1[E2/x]

where substitution in this context requires being careful so you won’t capture names. This requires you to be able to do another kind of transformation which is called “alpha conversion”, which basically says that you can rename identifiers as long as you keep the same binding structure (eg, a valid renaming does not change the de-Bruijn form of the expression). There is one more rule that can be used, eta conversion which says that (lambda (x) (f x)) is the same as f (we used this rule above when deriving the Y combinator).

One last difference between Schlac and Racket is that Schlac is a lazy language. This will be important since we do not have any built-in special forms like if.

Here is a Schlac definition for the identity function:

(define identity (lambda (x) x))

and there is not much that we can do with this now:

> identity
#<procedure:identity>
> (identity identity)
#<procedure:identity>
> (identity identity identity)
#<procedure:identity>

(In the last expression, note that (id id id) is shorthand for ((id id) id), and since (id id) is the identity, applying that on id returns it again.)

Church NumeralsTuesday, October 16th

So far, it seems like it is impossible to do anything useful in this language, since all we have are functions and applications. We know how to write the identity function, but what about other values? For example, can you write code that evaluates to zero?

What’s zero? I only know how to write functions!

(Turing Machine programmer: “What’s a function? — I only know how to write 0s and 1s!”)

The first thing we therefore need is to be able to encode numbers as functions. For zero, we will use a function of two arguments that simply returns its second value:

(define 0 (lambda (f) (lambda (x) x)))

or, more concisely

(define 0 (lambda (f x) x))

This is the first step in an encoding that is known as Church Numerals: an encoding of natural numbers as functions. The number zero is encoded as a function that takes in a function and a second value, and applies the function zero times on the argument (which is really what the above definition is doing). Following this view, the number one is going to be a function of two arguments, that applies the first on the second one time:

(define 1 (lambda (f x) (f x)))

and note that 1 is just like the identity function (as long as you give it a function as its first input, but this is always the case in Schlac). The next number on the list is two — which applies the first argument on the second one twice:

(define 2 (lambda (f x) (f (f x))))

We can go on doing this, but what we really want is a way to perform arbitrary arithmetic. The first requirement for that is an add1 function that increments its input (an encoded natural number) by one. To do this, we write a function that expects an encoded number:

(define add1 (lambda (n) ...))

and this function is expected to return an encoded number, which is always a function of f and x:

(define add1 (lambda (n) (lambda (f x) ...)))

Now, in the body, we need to apply f on x n+1 times — but remember that n is a function that will do n applications of its first argument on its second:

(define add1 (lambda (n) (lambda (f x) ... (n f x) ...)))

and all we have left to do now is to apply f one more time, yielding this definition for add1:

(define add1 (lambda (n) (lambda (f x) (f (n f x)))))

Using this, we can define a few useful numbers:

(define 1 (add1 0))
(define 2 (add1 1))
(define 3 (add1 2))
(define 4 (add1 3))
(define 5 (add1 4))

This is all nice theoretically, but how can we make sure that it is correct? Well, Schlac has a few additional special forms that translate Church numerals into Racket numbers. To try our definitions we use the ->nat (read: to natural number):

(->nat 0)
(->nat 5)
(->nat (add1 (add1 5)))

You can now verify that the identity function is really the same as the number 1:

(->nat identity)

We can even write a test case, since Schlac contains the test special form, but we have to be careful in that — first of all, we cannot test whether functions are equal (why?) so we must use ->nat, but

(test (->nat (add1 (add1 5))) => 7)

will not work since 7 is undefined. To overcome this, Schlac has a back-door for primitive Racket values — just use a quote:

(test (->nat (add1 (add1 5))) => '7)

We can now define natural number addition — one simple idea is to get two encoded numbers m and n, then start with x, apply f on it n times by using it as a function, then apply f m more times on the result in the same way:

(define + (lambda (m n) (lambda (f x) (m f (n f x)))))

or equivalently:

(define + (lambda (m n f x) (m f (n f x))))

Another idea is to use add1 and increment n by m using add1:

(define + (lambda (m n) (m add1 n)))
(->nat (+ 4 5))

We can also define multiplication of m and n quite easily — begin with addition — (lambda (x) (+ n x)) is a function that expects an x and returns (+ x n) — it’s an increment-by-n function. But since all functions and applications are curried, this is actually the same as (lambda (x) ((+ n) x)) which is the same as (+ n). Now, what we want to do is repeat this operation m times over zero, which will add n to zero m times, resulting in m * n. The definition is therefore:

(define * (lambda (m n) (m (+ n) 0)))
(->nat (* 4 5))
(->nat (+ 4 (* (+ 2 5) 5)))

An alternative approach is to consider

(lambda (x) (n f x))

for some encoded number n and a function f — this function is like f^n (f composed n times with itself). But remember that this is shorthand for

(lambda (x) ((n f) x))

and we know that (lambda (x) (foo x)) is just like foo (if it is a function), so this is equivalent to just

(n f)

So (n f) is f^n, and in the same way (m g) is g^m — if we use (n f) for g, we get (m (n f)) which is n self-compositions of f, self-composed m times. In other words, (m (n f)) is a function that is like m*n applications of f, so we can define multiplication as:

(define * (lambda (m n) (lambda (f) (m (n f)))))

which is the same as

(define * (lambda (m n f) (m (n f))))

The same principle can be used to define exponentiation (but now we have to be careful with the order since exponentiation is not commutative):

(define ^ (lambda (m n) (n (* m) 1)))
(->nat (^ 3 4))

And there is a similar alternative here too —

which basically says that any number encoding n is also the ?^n operation.

All of this is was not too complicated — but all so far all we did is write functions that increment their inputs in various ways. What about sub1? For that, we need to do some more work — we will need to encode booleans.

More EncodingsTuesday, October 16th

Our choice of encoding numbers makes sense — the idea is that the main feature of a natural number is repeating something a number of times. For booleans, the main property we’re looking for is choosing between two values. So we can encode true and false by functions of two arguments that return either the first or the second argument:

(define #t (lambda (x y) x))
(define #f (lambda (x y) y))

Note that this encoding of #f is really the same as the encoding of 0, so we have to know what type to expect an use the proper operations (this is similar to C, where everything is just integers). Now that we have these two, we can define if:

(define if (lambda (c t e) (c t e)))

it expects a boolean which is a function of two arguments, and passes it the two expressions. The #t boolean will simply return the first, and the #f boolean will return the second. Strictly speaking, we don’t really need this definition, since instead of writing (if c t e), we can simply write (c t e). In any case, we need the language to be lazy for this to work. To demonstrate this, we’ll intentionally use the quote back-door to use a non-functional value, using this will normally result in an error:

(+ '1 '2)

But testing our if definition, things work just fine:

(if #t (+ 4 5) (+ 1 2))

and we see that DrRacket leaves the second addition expression in red, which indicates that it was not executed. We can also make sure that even when it is defined as a function, it is still working fine because the language is lazy:

(if #f ((lambda (x) (x x)) (lambda (x) (x x))) 3)

What about and and or? Simple, or takes two arguments, and returns either true or false if one of the inputs is true:

(define or (lambda (a b) (if a #t (if b #t #f))))

but (if b #t #f) is really the same as just b because it must be a boolean (we cannot use more than one “truty” or “falsy” values):

(define or (lambda (a b) (if a #t b)))

also, if a is true, we want to return #t, but that is exactly the value of a, so:

(define or (lambda (a b) (if a a b)))

and finally, we can get rid of the if (which is actually breaking the if abstraction, if we encode booleans in some other way):

(define or (lambda (a b) (a a b)))

Similarly, you can convince yourself that the definition of and is:

(define and (lambda (a b) (a b a)))

Schlac has to-Racket conversion forms for booleans too:

(->bool (or #f #f))
(->bool (or #f #t))
(->bool (or #t #f))
(->bool (or #t #t))

and

(->bool (and #f #f))
(->bool (and #f #t))
(->bool (and #t #f))
(->bool (and #t #t))

A not function is quite simple — one alternative is to choose from true and false in the usual way:

(define not (lambda (a) (a #f #t)))

and another is to return a function that switches the inputs to an input boolean:

(define not (lambda (a) (lambda (x y) (a y x))))

which is the same as

(define not (lambda (a x y) (a y x)))

We can now put numbers and booleans together: we define a zero? function.

(define zero? (lambda (n) (n (lambda (x) #f) #t)))
(test (->bool (and (zero? 0) (not (zero? 3)))) => '#t)

(Good question: is this fast?)

(Note that it is better to test that the value is explicitly #t, if we just use (test (->bool ...)) then the test will work even if the expression in question evaluated to some bogus value.)

The idea is simple — if n is the encoding of zero, it will return it’s second argument which is #t:

(zero? 0) --> ((lambda (f n) n) (lambda (x) #f) #t) -> #t

if n is an encoding of a bigger number, then it is a self-composition, and the function that we give it is one that always returns #f, no matter how many times it is self-composed. Try 2 for example:

(zero? 2) --> ((lambda (f n) (f (f n))) (lambda (x) #f) #t)
          --> ((lambda (x) #f) ((lambda (x) #f) #t))
          --> #f

Now, how about an encoding for compound values? A minimal approach is what we use in Racket — a way to generate pairs (cons), and encode lists as chains of pairs with a special value at the end (null). There is a natural encoding for pairs that we have previously seen — a pair is a function that expects a selector, and will apply that on the two values:

(define cons (lambda (x y) (lambda (s) (s x y))))

Or, equivalently:

(define cons (lambda (x y s) (s x y)))

To extract the two values from a pair, we need to pass a selector that consumes two values and returns one of them. In our framework, this is exactly what the two boolean values do, so we get:

(define car (lambda (x) (x #t)))
(define cdr (lambda (x) (x #f)))

(->nat (+ (car (cons 2 3)) (cdr (cons 2 3))))

We can even do this:

(define 1st car)
(define 2nd (lambda (l) (car (cdr l))))
(define 3rd (lambda (l) (car (cdr (cdr l)))))
(define 4th (lambda (l) (car (cdr (cdr (cdr l))))))
(define 5th (lambda (l) (car (cdr (cdr (cdr (cdr l)))))))

or write a list-ref function:

(define list-ref (lambda (l n) (car (n cdr l))))

Note that we don’t need a recursive function for this: our encoding of natural numbers makes it easy to “iterate N times”. What we get with this encoding is essentially free natural-number recursion.

We now need a special null value to mark list ends. This value should have the same number of arguments as a cons value (one: a selector/boolean function), and it should be possible to distinguish it from other values. We choose

(define null (lambda (s) #t))

Testing the list encoding:

(define l123 (cons 1 (cons 2 (cons 3 null))))
(->nat (2nd l123))

And as with natural numbers and booleans, Schlac has built-in facility to convert encoded lists to Racket values, except that this requires specifying the type of values in a list so it’s a higher-order function:

((->listof ->nat) l123)

which (“as usual”) can be written as

(->listof ->nat l123)

We can even do this:

(->listof (->listof ->nat) (cons l123 (cons l123 null)))

Defining null? is now relatively easy (and it’s actually already used by the above ->listof conversion). The following definition

(define null? (lambda (x) (x (lambda (x y) #f))))

works because if x is null, then it simply ignores its argument and returns #t, and if it’s a pair, then it uses the input selector, which always returns #f in its turn. Using some arbitrary A and B:

(null? (cons A B))
  --> ((lambda (x) (x (lambda (x y) #f))) (lambda (s) (s A B)))
  --> ((lambda (s) (s A B)) (lambda (x y) #f))
  --> ((lambda (x y) #f) A B)
  --> #f
(null? null)
  --> ((lambda (x) (x (lambda (x y) #f))) (lambda (s) #t))
  --> ((lambda (s) #t) (lambda (x y) #f))
  --> #t

We can use the Y combinator to create recursive functions — we can even use the rewrite rules facility that Schlac contains (the same one that we have previously seen):

(define Y
  (lambda (f)
    ((lambda (x) (x x)) (lambda (x) (f (x x))))))
(rewrite (define/rec f E) => (define f (Y (lambda (f) E))))

and using it:

(define/rec length
  (lambda (l)
    (if (null? l)
      0
      (add1 (length (cdr l))))))
(->nat (length l123))

And to complete this, um, journey — we’re still missing subtraction. There are many ways to solve the problem of subtraction, and for a challenge try to come up with a solution yourself. One of the clearer solutions uses a simple idea — begin with a pair of two zeroes <0,0>, and repeat this transformation n times: <a,b> -> <b,b+1>. After n steps, we will have <n-1,n> — so we get:

(define inccons (lambda (p) (cons (cdr p) (add1 (cdr p)))))
(define sub1 (lambda (n) (car (n inccons (cons 0 0)))))
(->nat (sub1 5))

And from this the road is short to general subtraction, m-n is simply n applications of sub1 on m:

(define - (lambda (m n) (n sub1 m)))
(test (->nat (- 3 2)) => '1)
(test (->nat (- (* 4 (* 5 5)) 5)) => '95)

We now have a normal-looking language, and we’re ready to do anything we want. Here are two popular examples:

(define/rec fact
  (lambda (x)
    (if (zero? x) 1 (* x (fact (sub1 x))))))
(test (->nat (fact 5)) => '120)

(define/rec fib
  (lambda (x)
    (if (or (zero? x) (zero? (sub1 x)))
      1
      (+ (fib (- x 1)) (fib (- x 2))))))
(test (->nat (fib (* 5 2))) => '89)

To get generalized arithmetic capability, Schlac has yet another built-in facility for translating Racket natural numbers into Church numerals:

(->nat (fib (nat-> '10)))

… and to get to that frightening expression in the beginning, all you need to do is replace all definitions in the fib definition over and over again until you’re left with nothing but lambda expressions and applications, then reformat the result into some cute shape. For extra fun, you can look for immediate applications of lambda expressions and reduce them manually.

All of this is in the following code:

;; Making Schlac into a practical language (not an interpreter)

#lang pl schlac

(define identity (lambda (x) x))

;; Natural numbers

(define 0 (lambda (f x) x))

(define add1 (lambda (n) (lambda (f x) (f (n f x)))))
;; same as:
;;  (define add1 (lambda (n) (lambda (f x) (n f (f x)))))

(define 1 (add1 0))
(define 2 (add1 1))
(define 3 (add1 2))
(define 4 (add1 3))
(define 5 (add1 4))
(test (->nat (add1 (add1 5))) => '7)

(define + (lambda (m n) (m add1 n)))
(test (->nat (+ 4 5)) => '9)

;; (define * (lambda (m n) (m (+ n) 0)))
(define * (lambda (m n f) (m (n f))))
(test (->nat (* 4 5)) => '20)
(test (->nat (+ 4 (* (+ 2 5) 5))) => '39)

;; (define ^ (lambda (m n) (n (* m) 1)))
(define ^ (lambda (m n) (n m)))
(test (->nat (^ 3 4)) => '81)

;; Booleans

(define #t (lambda (x y) x))
(define #f (lambda (x y) y))

(define if (lambda (c t e) (c t e))) ; not really needed

(test (->nat (if #t 1 2)) => '1)
(test (->nat (if #t (+ 4 5) (+ '1 '2))) => '9)

(define and (lambda (a b) (a b a)))
(define or  (lambda (a b) (a a b)))
;; (define not (lambda (a) (a #f #t)))
(define not (lambda (a x y) (a y x)))

(test (->bool (and #f #f)) => '#f)
(test (->bool (and #t #f)) => '#f)
(test (->bool (and #f #t)) => '#f)
(test (->bool (and #t #t)) => '#t)
(test (->bool (or  #f #f)) => '#f)
(test (->bool (or  #t #f)) => '#t)
(test (->bool (or  #f #t)) => '#t)
(test (->bool (or  #t #t)) => '#t)
(test (->bool (not #f)) => '#t)
(test (->bool (not #t)) => '#f)

(define zero? (lambda (n) (n (lambda (x) #f) #t)))
(test (->bool (and (zero? 0) (not (zero? 3)))) => '#t)

;; Lists

(define cons (lambda (x y s) (s x y)))

(define car (lambda (x) (x #t)))
(define cdr (lambda (x) (x #f)))

(test (->nat (+ (car (cons 2 3)) (cdr (cons 2 3)))) => '5)

(define 1st car)
(define 2nd (lambda (l) (car (cdr l))))
(define 3rd (lambda (l) (car (cdr (cdr l)))))
(define 4th (lambda (l) (car (cdr (cdr (cdr l))))))
(define 5th (lambda (l) (car (cdr (cdr (cdr (cdr l)))))))

(define null (lambda (s) #t))
(define null? (lambda (x) (x (lambda (x y) #f))))

(define l123 (cons 1 (cons 2 (cons 3 null))))
;; Note that `->listof' is a H.O. converter
(test ((->listof ->nat) l123) => '(1 2 3))
(test (->listof ->nat l123) => '(1 2 3))  ; same as the above
(test (->listof (->listof ->nat) (cons l123 (cons l123 null)))
      => '((1 2 3) (1 2 3)))

;; Subtraction is tricky

(define inccons (lambda (p) (cons (cdr p) (add1 (cdr p)))))
(define sub1 (lambda (n) (car (n inccons (cons 0 0)))))

(test (->nat (sub1 5)) => '4)

(define - (lambda (a b) (b sub1 a)))

(test (->nat (- 3 2)) => '1)
(test (->nat (- (* 4 (* 5 5)) 5)) => '95)
(test (->nat (- 2 4)) => '0) ; this is "natural subtraction"

;; Recursive functions

(define Y
  (lambda (f)
    ((lambda (x) (x x)) (lambda (x) (f (x x))))))
(rewrite (define/rec f E) => (define f (Y (lambda (f) E))))

(define/rec length
  (lambda (l)
    (if (null? l)
      0
      (add1 (length (cdr l))))))
(test (->nat (length l123)) => '3)

(define/rec fact
  (lambda (x)
    (if (zero? x) 1 (* x (fact (sub1 x))))))
(test (->nat (fact 5)) => '120)

(define/rec fib
  (lambda (x)
    (if (or (zero? x) (zero? (sub1 x)))
      1
      (+ (fib (sub1 x)) (fib (sub1 (sub1 x)))))))
(test (->nat (fib (* 5 2))) => '89)

#|
;; Fully-expanded Fibonacci
(define fib
  ((lambda (f)
    ((lambda (x) (x x)) (lambda (x) (f (x x)))))
  (lambda (f)
    (lambda (x)
      ((lambda (c t e) (c t e))
        ((lambda (a b) (a a b))
        ((lambda (n)
            (n (lambda (x) (lambda (x y) y)) (lambda (x y) x)))
          x)
        ((lambda (n)
            (n (lambda (x) (lambda (x y) y)) (lambda (x y) x)))
          ((lambda (n)
            ((lambda (x) (x (lambda (x y) x)))
              (n (lambda (p)
                  ((lambda (x y s) (s x y))
                    ((lambda (x) (x (lambda (x y) y))) p)
                    ((lambda (n) (lambda (f x) (f (n f x))))
                    ((lambda (x) (x (lambda (x y) y))) p))))
                ((lambda (x y s) (s x y))
                  (lambda (f x) x)
                  (lambda (f x) x)))))
          x)))
        ((lambda (n) (lambda (f x) (f (n f x)))) (lambda (f x) x))
        ((lambda (x y)
          (x (lambda (n) (lambda (f x) (f (n f x)))) y))
        (f ((lambda (n)
              ((lambda (x) (x (lambda (x y) x)))
                (n (lambda (p)
                    ((lambda (x y s) (s x y))
                      ((lambda (x) (x (lambda (x y) y))) p)
                      ((lambda (n) (lambda (f x) (f (n f x))))
                      ((lambda (x) (x (lambda (x y) y))) p))))
                  ((lambda (x y s) (s x y))
                    (lambda (f x) x)
                    (lambda (f x) x)))))
            x))
        (f ((lambda (n)
              ((lambda (x) (x (lambda (x y) x)))
                (n (lambda (p)
                    ((lambda (x y s) (s x y))
                      ((lambda (x) (x (lambda (x y) y))) p)
                      ((lambda (n) (lambda (f x) (f (n f x))))
                      ((lambda (x) (x (lambda (x y) y))) p))))
                  ((lambda (x y s) (s x y))
                    (lambda (f x) x)
                    (lambda (f x) x)))))
            ((lambda (n)
                ((lambda (x) (x (lambda (x y) x)))
                (n (lambda (p)
                      ((lambda (x y s) (s x y))
                      ((lambda (x) (x (lambda (x y) y))) p)
                      ((lambda (n) (lambda (f x) (f (n f x))))
                        ((lambda (x) (x (lambda (x y) y))) p))))
                    ((lambda (x y s) (s x y))
                    (lambda (f x) x)
                    (lambda (f x) x)))))
              x)))))))))

;; The same after reducing all immediate function applications
(define fib
  ((lambda (f)
    ((lambda (x) (x x)) (lambda (x) (f (x x)))))
  (lambda (f)
    (lambda (x)
      (((x (lambda (x) (lambda (x y) y)) (lambda (x y) x))
        (x (lambda (x) (lambda (x y) y)) (lambda (x y) x))
        (((x (lambda (p)
                (lambda (s)
                  (s (p (lambda (x y) y))
                    (lambda (f x)
                      (f ((p (lambda (x y) y)) f x))))))
              (lambda (s)
                (s (lambda (f x) x) (lambda (f x) x))))
          (lambda (x y) x))
          (lambda (x) (lambda (x y) y))
          (lambda (x y) x)))
        (lambda (f x) (f x))
        ((f ((x (lambda (p)
                  (lambda (s)
                    (s (p (lambda (x y) y))
                      (lambda (f x)
                        (f ((p (lambda (x y) y)) f x))))))
                (lambda (y s)
                  (s (lambda (f x) x) (lambda (f x) x))))
            (lambda (x y) x)))
        (lambda (n) (lambda (f x) (f (n f x))))
        (f ((((x (lambda (p)
                    (lambda (s)
                      (s (p (lambda (x y) y))
                        (lambda (f x)
                          (f ((p (lambda (x y) y)) f x))))))
                  (lambda (s)
                    (s (lambda (f x) x) (lambda (f x) x))))
              (lambda (x y) x))
              (lambda (p)
                (lambda (s)
                  (s (p (lambda (x y) y))
                    (lambda (f x)
                      (f ((p (lambda (x y) y)) f x))))))
              (lambda (s)
                (s (lambda (f x) x) (lambda (f x) x))))
            (lambda (x y) x)))))))))

;; Cute reformatting of the above:
(define fib((lambda(f)((lambda(x)(x x))(lambda(x)(f(x x)))))(lambda(
f)(lambda(x)(((x(lambda(x)(lambda(x y)y))(lambda(x y)x))(x(lambda(x)
(lambda(x y)y))(lambda(x y) x))(((x(lambda(p)(lambda(s)(s(p(lambda(x
y)y))(lambda(f x)(f((p(lambda(x y)y))f x))))))(lambda(s) (s(lambda(f
x)x)(lambda(f x)x))))(lambda(x y)x))(lambda(x)(lambda(x y)y))(lambda
(x y)x)))(lambda(f x)(f x))((f((x(lambda(p)(lambda(s)(s(p(lambda(x y
)y))(lambda(f x)(f((p(lambda(x y)y))f x))))))(lambda(y s)(s(lambda(f
x)x)(lambda(f x)x))))(lambda(x y)x)))(lambda(n)(lambda(f x)(f(n f x)
)))(f((((x(lambda(p)(lambda(s)(s(p (lambda(x y)y))(lambda(f x)(f((p(
lambda(x y) y))f x))))))(lambda(s)(s(lambda(f x)x)(lambda(f x)x))))(
;;                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
;;                      `---------------(cons 0 0)---------------'
lambda(x y)x))(lambda(p)(lambda(s)(s(p(lambda(x y)y))(lambda(f x)(f(
(p(lambda(x y)y))f x))))))(lambda(s)(s(lambda(f x)x)(lambda(f x)x)))
)(lambda(x y)x)))))))))

And for extra fun:

        (λ(f)(λ
        (x)(((x(λ(
        x)(λ(x y)y)
        )(λ(x y)x))(
        x(λ(x)(λ(x y)
            y))(λ(x y
              )x))(((
                x(λ(p)(
                λ(s)(s
                (p (λ(
                x y)y))
                  (λ(f x
                  )(f((p(
                  λ(x y)
                  y))f x
                  ))))))(
                  λ(s)(s(
                  λ(f x)x)
                  (λ(f x)x)
                )))(λ(x y)
                x))(λ(x)(λ(
                x y)y)) (λ(
                x y) x)))(λ(
                f x)(f x))((f
              ((x(λ(p )(λ (s
              )(s(p(  λ(x y)
              y))(λ (  f x)(f(
              (p (λ(    x y)y)
            )f x)))    )))(λ(
            y s)(s    (λ (f x
            )x)(λ(      f x)x)
            )))(λ(      x y)x))
            )(λ(n)        (λ (f
          x)(f (n        f x)))
          )(f(((        (x(λ(p)
          (λ(s)(s          (p( λ(
          x y )y          ))(λ(f
        x) (f((          p(λ(x y
        )y)) f            x)))))
        )(λ(s)(            s(λ(f x
        )x)(λ(              f x)x)
        ))) (λ              (x y)x
      ))(λ(p                )(λ(s)(
      s(p(λ(                x y)y)
      )(λ (f                  x)(f((
      p(λ (x                  y)y)) f
    x))))))                  (λ(s)(
    s(λ (f                    x)x)(λ
    (f x)x)                    )))(λ(
    x y)x)                      ))))))

|#

Alternative Church EncodingTuesday, October 23rd

Finally, note that this is just one way to encode things — other encodings are possible. One alternative encoding is in the following code — it uses a list of N falses as the encoding for N. This encoding makes it easier to add1 (just cons another #f), and to sub1 (simply cdr). The tradeoff is that some arithmetics operations becomes more complicated, for example, the definition of + requires the fixpoint combinator. (As expected, some people want to see what can we do with a language without recursion, so they don’t like jumping to Y too fast.)

;; An alternative "Church" encoding: use lists to encode numbers

#lang pl schlac

(define identity (lambda (x) x))

;; Booleans (same as before)

(define #t (lambda (x y) x))
(define #f (lambda (x y) y))

(define if (lambda (c t e) (c t e))) ; not really needed

(test (->bool (if #t #f #t))
      => '#f)
(test (->bool (if #f ((lambda (x) (x x)) (lambda (x) (x x))) #t))
      => '#t)

(define and (lambda (a b) (a b a)))
(define or  (lambda (a b) (a a b)))
(define not (lambda (a x y) (a y x)))

(test (->bool (and #f #f)) => '#f)
(test (->bool (and #t #f)) => '#f)
(test (->bool (and #f #t)) => '#f)
(test (->bool (and #t #t)) => '#t)
(test (->bool (or  #f #f)) => '#f)
(test (->bool (or  #t #f)) => '#t)
(test (->bool (or  #f #t)) => '#t)
(test (->bool (or  #t #t)) => '#t)
(test (->bool (not #f)) => '#t)
(test (->bool (not #t)) => '#f)

;; Lists (same as before)

(define cons (lambda (x y s) (s x y)))
(define car (lambda (x) (x #t)))
(define cdr (lambda (x) (x #f)))

(define 1st car)
(define 2nd (lambda (l) (car (cdr l))))
(define 3rd (lambda (l) (car (cdr (cdr l)))))
(define 4th (lambda (l) (car (cdr (cdr (cdr l))))))
(define 5th (lambda (l) (car (cdr (cdr (cdr (cdr l)))))))

(define null (lambda (s) #t))
(define null? (lambda (x) (x (lambda (x y) #f))))

;; Natural numbers (alternate encoding)

(define 0 identity)

(define add1 (lambda (n) (cons #f n)))

(define zero? car) ; tricky

(define sub1 cdr) ; this becomes very simple

;; Note that we could have used something more straightforward:
;; (define 0 null)
;; (define add1 (lambda (n) (cons #t n))) ; cons anything
;; (define zero? null?)
;; (define sub1 (lambda (l) (if (zero? l) l (cdr l))))

(define 1 (add1 0))
(define 2 (add1 1))
(define 3 (add1 2))
(define 4 (add1 3))
(define 5 (add1 4))

(test (->nat* (add1 (add1 5))) => '7)
(test (->nat* (sub1 (sub1 (add1 (add1 5))))) => '5)
(test (->bool (and (zero? 0) (not (zero? 3)))) => '#t)
(test (->bool (zero? (sub1 (sub1 (sub1 3))))) => '#t)

;; list-of-numbers tests
(define l123 (cons 1 (cons 2 (cons 3 null))))
(test (->listof ->nat* l123) => '(1 2 3))
(test (->listof (->listof ->nat*) (cons l123 (cons l123 null)))
      => '((1 2 3) (1 2 3)))

;; Recursive functions

(define Y
  (lambda (f)
    ((lambda (x) (x x)) (lambda (x) (f (x x))))))
(rewrite (define/rec f E) => (define f (Y (lambda (f) E))))

;; note that this example is doing something silly now
(define/rec length
  (lambda (l)
    (if (null? l)
      0
      (add1 (length (cdr l))))))
(test (->nat* (length l123)) => '3)

;; addition becomes hard since it requires a recursive definition
;; (define/rec +
;;  (lambda (m n) (if (zero? n) m (+ (add1 m) (sub1 n)))))
;; (test (->nat* (+ 4 5)) => '9)

;; faster alternative:
(define/rec +
  (lambda (m n)
    (if (zero? m) n
        (if (zero? n) m
            (add1 (add1 (+ (sub1 m) (sub1 n))))))))
(test (->nat* (+ 4 5)) => '9)

;; subtraction is similar to addition
;; (define/rec -
;;  (lambda (m n) (if (zero? n) m (- (sub1 m) (sub1 n)))))
;; (test (->nat* (- (+ 4 5) 4)) => '5)
;; but this is not "natural subtraction": doesn't work when n>m,
;; because (sub1 0) does not return 0.

;; a solution is like alternative form of +:
(define/rec -
  (lambda (m n)
    (if (zero? m) 0
        (if (zero? n) m
            (- (sub1 m) (sub1 n))))))
(test (->nat* (- (+ 4 5) 4)) => '5)
(test (->nat* (- 2 5)) => '0)
;; alternatively, could change sub1 above:
;; (define sub1 (lambda (n) (if (zero? n) n (cdr n))))

;; we can do multiplication in a similar way
(define/rec *
  (lambda (m n)
    (if (zero? m) 0
        (+ n (* (sub1 m) n)))))
(test (->nat* (* 4 5)) => '20)
(test (->nat* (+ 4 (* (+ 2 5) 5))) => '39)

;; and the rest of the examples

(define/rec fact
  (lambda (x)
    (if (zero? x) 1 (* x (fact (sub1 x))))))
(test (->nat* (fact 5)) => '120)

(define/rec fib
  (lambda (x)
    (if (or (zero? x) (zero? (sub1 x)))
      1
      (+ (fib (sub1 x)) (fib (sub1 (sub1 x)))))))
(test (->nat* (fib (* 5 2))) => '89)

#|
;; Fully-expanded Fibonacci (note: much shorter than the previous
;; encoding, but see how Y appears twice -- two "((lambda" pairs)
(define fib((lambda(f)((lambda(x)(x x))(lambda(x)(f(x x)))))(lambda(
f)(lambda(x)(((((x(lambda(x y)x))(x(lambda(x y)x)))((x(lambda(x y)y)
)(lambda(x y)x)))(lambda(s)(s(lambda(x y)y)(lambda(x)x))))((((lambda
(f)((lambda(x)(x x))(lambda(x)(f(x x))))) (lambda(f)(lambda(m n)((m(
lambda(x y)x))n (((n(lambda(x y)x)) m)(lambda(s)((s (lambda(x y)y))(
lambda(s)((s (lambda(x y)y))((f(m(lambda(x y)y)))(n(lambda(x y)y))))
))))))))(f(x(lambda(x y)y))))(f((x(lambda(x y)y))(lambda(x y)y))))))
)))
|#

Another interesting way to implement lists follows the pattern matching approach, where both pairs and the null value are represented by a function that serves as a kind of a match dispatcher. This function takes in two inputs — if it is the representation of null then it will return the first input, and if it is a pair, then it will apply the second input on the two parts of the pair. This is implemented as follows:

(define null
  (lambda (n p)
    n))

(define cons
  (lambda (x y)
    (lambda (n p)
      (p x y))))

This might seem awkward, but it follows the intended use of pairs and null as a match-like construct. Here is an example, with the equivalent Racket code on the side:

;; Sums up a list of numbers
(define (sum l)
  (l                    ; (match l
  0                    ;  ['() 0]
  (lambda (x xs)      ;  [(cons x xs)
    (+ x (sum xs)))))  ;    (+ x (sum xs))])

In fact, it’s easy to implement our selectors and predicate using this:

(define null? (lambda (l) (l #t (lambda (x xs) #f))))
(define car  (lambda (l) (l #f (lambda (x y) x))))
(define cdr  (lambda (l) (l #f (lambda (x y) y))))
;; in the above `#f' is really any value, since it
;; should be an error alternatively:
(define car (lambda (l)
              (l ((lambda (x) (x x)) (lambda (x) (x x))) ; "error"
                (lambda (x y) x))))

The same approach can be used to define any kind of new data type in a way that looks like our own define-type definitions. For example, consider a much-simplified definition of the AE type we’ve seen early in the semester, and a matching eval definition as an example for using cases:

(define-type AE
  [Num Number]
  [Add AE AE])
(: eval : AE -> Number)
(define (eval expr)
  (cases expr
    [(Num n)  n]
    [(Add l r) (+ (eval l) (eval r))]))

We can follow the above approach now to write Schlac code that more than being equivalent, it’s also very similar in nature. Note that the type definition is replaced by two definitions for the two constructors:

(define Num (lambda (n)  (lambda (num add) (num n  ))))
(define Add (lambda (l r) (lambda (num add) (add l r))))
(define eval
  (lambda (expr) ; `expr` is always a (lambda (num add) ...), and it
                ; expects a unary `num` argument and a binary `add`
    (expr (lambda (n)  n)
          (lambda (l r) (+ (eval l) (eval r))))))

Recursive EnvironmentsTuesday, October 23rd

PLAI §11.5

What we really need for recursion, is a special kind of an environment, one that can refer to itself. So instead of doing (note: calls removed for readability):

{with {fact {fun {n}
              {if {zero? n} 1 {* n {fact {- n 1}}}}}}
  {fact 5}}

which does not work for the usual reasons, we want to use some

{rec {fact {fun {n}
            {if {zero? n} 1 {* n {fact {- n 1}}}}}}
  {fact 5}}

that will do the necessary magic.

One way to achieve this is using the Y combinator as we have seen — a kind of a “constructor” for recursive functions. We can do that in a similar way to the rewrite rule that we have seen in Schlac — translate the above expression to:

{with {fact {make-rec
              {fun {fact}
                {fun {n}
                  {if {zero? n} 1 {* n {fact {- n 1}}}}}}}}
  {fact 5}}

or even:

{with {fact {{fun {f} {{fun {x} {f {x x}}} {fun {x} {f {x x}}}}}
            {fun {fact}
              {fun {n}
                {if {zero? n} 1 {* n {fact {- n 1}}}}}}}}
  {fact 5}}

Now, we will see how it can be used in our code to implement a recursive environment.

If we look at what with does in

{with {fact {fun {n}
              {if {zero? n} 1 {* n {call fact {- n 1}}}}}}
  {call fact 5}}

then we can say that to evaluate this expression, we evaluate the body expression in an extended environment that contains fact, even if a bogus one that is good for 0 only — the new environment is created with something like this:

extend("fact", make-fact-closure(), env)

so we can take this whole thing as an operation over env

add-fact(env) := extend("fact", make-fact-closure(), env)

This gives us the first-level fact. But fact itself is still undefined in env, so it cannot call itself. We can try this:

add-fact(add-fact(env))

but that still doesn’t work, and it will never work no matter how far we go:

add-fact(add-fact(add-fact(add-fact(add-fact(...env...)))))

What we really want is infinity: a place where add-fact works and the result is the same as what we’ve started with — we want to create a “magical” environment that makes this possible:

let magic-env = ???
such that:
  add-fact(magic-env) = magic-env

which basically gives us the illusion of being at the infinity point. This magic-env thing is exactly the fixed-point of the add-fact operation. We can use:

magic-env = rec(add-fact)

and following the main property of the Y combinator, we know that:

magic-env = rec(add-fact)          ; def. of magic-env
          = add-fact(rec(add-fact)) ; Y(f) = f(Y(f))
          = add-fact(magic-env)    ; def. of magic-env

What does all this mean? It means that if we have a fixed-point operator at the level of the implementation of our environments, then we can use it to implement a recursive binder. In our case, this means that a fixpoint in Racket can be used to implement a recursive language. But we have that — Racket does have recursive functions, so we should be able to use that to implement our recursive binder.

There are two ways that make it possible to write recursive functions in Racket. One is to define a function, and use its name to do a recursive call — using the Racket formal rules, we can see that we said that we mark that we now know that a variable is bound to a value. This is essentially a side-effect — we modify what we know, which corresponds to modifying the global environment. The second way is a new form: letrec. This form is similar to let, except that the scope that is established includes the named expressions — it is exactly what we want rec to do. A third way is using recursive local definitions, but that is equivalent to using letrec, more on this soon.

Recursion: Racket’s letrecTuesday, October 23rd

So we want to add recursion to our language, practically. We already know that Racket makes it possible to write recursive functions, which is possible because of the way it implements its “global environment”: our evaluator can only extend an environment, while Racket modifies its global environment. This means that whenever a function is defined in the global environment, the resulting closure will have it as its environment “pointer”, but the global environment was not extended — it stays the same, and was just modified with one additional binding.

But Racket has another, a bit more organized way of using recursion: there is a special local-binding construct that is similar to let, but allows a function to refer to itself. It is called letrec:

(letrec ([fact (lambda (n)
                (if (zero? n)
                  1
                  (* n (fact (- n 1)))))])
  (fact 5))

Some people may remember that there was a third way for creating recursive functions: using local definition in function bodies. For example, we have seen things like:

(define (length list)
  (define (helper list len)
    (if (null? list)
      len
      (helper (rest list) (+ len 1))))
  (helper list 0))

This looks like the same kind of environment magic that happens with a global define — but actually, Racket defines the meaning of internal definitions using letrec — so the above code is exactly the same as:

(define (length list)
  (letrec ([helper (lambda (list len)
                    (if (null? list)
                      len
                      (helper (rest list) (+ len 1))))])
    (helper list 0)))

The scoping rules for a letrec is that the scope of the bound name covers both the body and the named expression. Furthermore, multiple names can be bound to multiple expressions, and the scope of each name covers all named expression as well as the body. This makes it easy to define mutually recursive functions, such as:

(letrec ([even? (lambda (n) (if (zero? n) #t (odd?  (- n 1))))]
        [odd?  (lambda (n) (if (zero? n) #f (even? (- n 1))))])
  (even? 99))

But it is not a required functionality — it could be done with a single recursive binding that contains several functions:

(letrec ([even+odd
          (list (lambda (n)
                  (if (zero? n) #t ((second even+odd) (- n 1))))
                (lambda (n)
                  (if (zero? n) #f ((first  even+odd) (- n 1)))))])
  ((first even+odd) 99))

This is basically the same problem we face if we want to use the Y combinator for mutually recursive bindings. The above solution is inconvenient, but it can be improved using more lets to have easier name access. For example:

(letrec ([even+odd
          (list (lambda (n)
                  (let ([even? (first  even+odd)]
                        [odd?  (second even+odd)])
                    (if (zero? n) #t (odd? (- n 1)))))
                (lambda (n)
                  (let ([even? (first  even+odd)]
                        [odd?  (second even+odd)])
                    (if (zero? n) #f (even? (- n 1))))))])
  (let ([even? (first  even+odd)]
        [odd?  (second even+odd)])
    (even? 99)))

Implementing Recursion using letrecTuesday, October 23rd

We will see how to add a similar construct to our language — for simplicity, we will add a rec form that handles a single binding:

{rec {fact {fun {n}
            {if {= 0 n}
              1
              {* n {fact {- n 1}}}}}}
  {fact 5}}

Using this, things can get a little tricky. What should we get if we do:

{rec {x x} x}

? Currently, it seems like there is no point in using any expression except for a function expression in a rec expression, so we will handle only these cases.

(BTW, under what circumstances would non-function values be useful in a letrec?)


One way to achieve this is to use the same trick that we have recently seen: instead of re-implementing language features, we can use existing features in our own language, which hopefully has the right functionality in a form that can be re-used to in our evaluator.

Previously, we have seen a way to implement environments using Racket closures:

;; Define a type for functional environments
(define-type ENV = Symbol -> VAL)

(: EmptyEnv : -> ENV)
(define (EmptyEnv)
  (lambda (id) (error 'lookup "no binding for ~s" id)))

(: lookup : Symbol ENV -> VAL)
(define (lookup name env)
  (env name))

(: Extend : Symbol VAL ENV -> ENV)
(define (Extend id val rest-env)
  (lambda (name)
    (if (eq? name id)
      val
      (rest-env name))))

We can use this implementation, and create circular environments using Racket’s letrec. The code for handling a with expressions is:

[(With bound-id named-expr bound-body)
(eval bound-body
      (Extend bound-id (eval named-expr env) env))]

It looks like we should be able to handle rec in a similar way (the AST constructor name is WRec (“with-rec”) so it doesn’t collide with TR’s Rec constructor for recursive types):

[(WRec bound-id named-expr bound-body)
(eval bound-body
      (Extend bound-id (eval named-expr env) env))]

but this won’t work because the named expression is evaluated prematurely, in the previous environment. Instead, we will move everything that needs to be done, including evaluation, to a separate extend-rec function:

[(WRec bound-id named-expr bound-body)
(eval bound-body
      (extend-rec bound-id named-expr env))]

Now, the extend-rec function needs to provide the new, “magically circular” environment. Following what we know about the arguments to extend-rec, and the fact that it returns a new environment (= a lookup function), we can sketch a rough definition:

(: extend-rec : Symbol FLANG ENV -> ENV) ; FLANG, not VAL!
;; extend an environment with a new binding that is the result of
;; evaluating an expression in the same environment as the extended
;; result
(define (extend-rec id expr rest-env)
  (lambda (name)
    (if (eq? name id)
      ... something that uses expr to get a value ...
      (rest-env name))))

What should the missing expression be? It can simply evaluate the object given itself:

(define (extend-rec id expr rest-env)
  (lambda (name)
    (if (eq? name id)
      (eval expr ...this environment...)
      (rest-env name))))

But how do we get this environment, before it is defined? Well, the environment is itself a Racket function, so we can use Racket’s letrec to make the function refer to itself recursively:

(define (extend-rec id expr rest-env)
  (letrec ([rec-env (lambda (name)
                      (if (eq? name id)
                        (eval expr rec-env)
                        (rest-env name)))])
    rec-env))

It’s a little more convenient to use an internal definition, and add a type for clarity:

(define (extend-rec id expr rest-env)
  (: rec-env : Symbol -> VAL)
  (define (rec-env name)
    (if (eq? name id)
      (eval expr rec-env)
      (rest-env name)))
  rec-env)

This works, but there are several problems:

  1. First, we no longer do a simple lookup in the new environment. Instead, we evaluate the expression on every such lookup. This seems like a technical point, because we do not have side-effects in our language (also because we said that we want to handle only function expressions). Still, it wastes space since each evaluation will allocate a new closure.

  2. Second, a related problem — what happens if we try to run this:

    {rec {x x} x}

    ? Well, we do that stuff to extend the current environment, then evaluate the body in the new environment, this body is a single variable reference:

    (eval (Id 'x) the-new-env)

    so we look up the value:

    (lookup 'x the-new-env)

    which is:

    (the-new-env 'x)

    which goes into the function which implements this environment, there we see that name is the same as name1, so we return:

    (eval expr rec-env)

    but the expr here is the original named-expression which is itself (Id 'x), and we’re in an infinite loop.

We can try to get over these problems using another binding. Racket allows several bindings in a single letrec expression or multiple internal function definitions, so we change extend-rec to use the newly-created environment:

(define (extend-rec id expr rest-env)
  (: rec-env : Symbol -> VAL)
  (define (rec-env name)
    (if (eq? name id)
      val
      (rest-env name)))
  (: val : VAL)
  (define val (eval expr rec-env))
  rec-env)

This runs into an interesting type error, which complains about possibly getting some Undefined value. It does work if we switch to the untyped language for now (using #lang pl untyped) — and it seems to run fine too. But it raises more questions, beginning with: what is the meaning of:

(letrec ([x ...]
        [y ...x...])
  ...)

or equivalently, an internal block of

(define x ...)
(define y ...x...)

? Well, DrRacket seems to do the “right thing” in this case, but what about:

(letrec ([y ...x...]
        [x ...])
  ...)

? As a hint, see what happens when we now try to evaluate the problematic

{rec {x x} x}

expression, and compare that with the result that you’d get from Racket. This also clarifies the type error that we received.

It should be clear now why we want to restrict usage to just binding recursive functions. There are no problems with such definitions because when we evaluate a fun expression, there is no evaluation of the body, which is the only place where there are potential references to the same function that is defined — a function’s body is delayed, and executed only when the function is applied later.

But the biggest question that is still open: we just implemented a circular environment using Racket’s own circular environment implementation, and that does not explain how they are actually implemented. The cycle of pointers that we’ve implemented depends on the cycle of pointers that Racket uses, and that is a black box we want to open up.

For reference, the complete code is below.

#lang pl

#|
The grammar:
  <FLANG> ::= <num>
            | { + <FLANG> <FLANG> }
            | { - <FLANG> <FLANG> }
            | { * <FLANG> <FLANG> }
            | { / <FLANG> <FLANG> }
            | { with { <id> <FLANG> } <FLANG> }
            | { rec { <id> <FLANG> } <FLANG> }
            | <id>
            | { fun { <id> } <FLANG> }
            | { call <FLANG> <FLANG> }

Evaluation rules:
  eval(N,env)                = N
  eval({+ E1 E2},env)        = eval(E1,env) + eval(E2,env)
  eval({- E1 E2},env)        = eval(E1,env) - eval(E2,env)
  eval({* E1 E2},env)        = eval(E1,env) * eval(E2,env)
  eval({/ E1 E2},env)        = eval(E1,env) / eval(E2,env)
  eval(x,env)                = lookup(x,env)
  eval({with {x E1} E2},env) = eval(E2,extend(x,eval(E1,env),env))
  eval({rec {x E1} E2},env)  = ???
  eval({fun {x} E},env)      = <{fun {x} E}, env>
  eval({call E1 E2},env1)
          = eval(Ef,extend(x,eval(E2,env1),env2))
                            if eval(E1,env1) = <{fun {x} Ef}, env2>
          = error!          otherwise
|#

(define-type FLANG
  [Num  Number]
  [Add  FLANG FLANG]
  [Sub  FLANG FLANG]
  [Mul  FLANG FLANG]
  [Div  FLANG FLANG]
  [Id  Symbol]
  [With Symbol FLANG FLANG]
  [WRec Symbol FLANG FLANG]
  [Fun  Symbol FLANG]
  [Call FLANG FLANG])

(: parse-sexpr : Sexpr -> FLANG)
;; parses s-expressions into FLANGs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(cons 'with more)
    (match sexpr
      [(list 'with (list (symbol: name) named) body)
        (With name (parse-sexpr named) (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `with' syntax in ~s" sexpr)])]
    [(cons 'rec more)
    (match sexpr
      [(list 'rec (list (symbol: name) named) body)
        (WRec name (parse-sexpr named) (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `rec' syntax in ~s" sexpr)])]
    [(cons 'fun more)
    (match sexpr
      [(list 'fun (list (symbol: name)) body)
        (Fun name (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `fun' syntax in ~s" sexpr)])]
    [(list '+ lhs rhs) (Add (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '- lhs rhs) (Sub (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '* lhs rhs) (Mul (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '/ lhs rhs) (Div (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list 'call fun arg)
                      (Call (parse-sexpr fun) (parse-sexpr arg))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

(: parse : String -> FLANG)
;; parses a string containing a FLANG expression to a FLANG AST
(define (parse str)
  (parse-sexpr (string->sexpr str)))

;; Types for environments, values, and a lookup function

(define-type VAL
  [NumV Number]
  [FunV Symbol FLANG ENV])

;; Define a type for functional environments
(define-type ENV = Symbol -> VAL)

(: EmptyEnv : -> ENV)
(define (EmptyEnv)
  (lambda (id) (error 'lookup "no binding for ~s" id)))

(: lookup : Symbol ENV -> VAL)
;; lookup a symbol in an environment, return its value or throw an
;; error if it isn't bound
(define (lookup name env)
  (env name))

(: Extend : Symbol VAL ENV -> ENV)
;; extend a given environment cache with a new binding
(define (Extend id val rest-env)
  (lambda (name)
    (if (eq? name id)
      val
      (rest-env name))))

(: extend-rec : Symbol FLANG ENV -> ENV)
;; extend an environment with a new binding that is the result of
;; evaluating an expression in the same environment as the extended
;; result
(define (extend-rec id expr rest-env)
  (: rec-env : Symbol -> VAL)
  (define (rec-env name)
    (if (eq? name id)
      val
      (rest-env name)))
  (: val : VAL)
  (define val (eval expr rec-env))
  rec-env)

(: NumV->number : VAL -> Number)
;; convert a FLANG runtime numeric value to a Racket one
(define (NumV->number val)
  (cases val
    [(NumV n) n]
    [else (error 'arith-op "expected a number, got: ~s" val)]))

(: arith-op : (Number Number -> Number) VAL VAL -> VAL)
;; gets a Racket numeric binary operator, and uses it within a NumV
;; wrapper
(define (arith-op op val1 val2)
  (NumV (op (NumV->number val1) (NumV->number val2))))

(: eval : FLANG ENV -> VAL)
;; evaluates FLANG expressions by reducing them to values
(define (eval expr env)
  (cases expr
    [(Num n) (NumV n)]
    [(Add l r) (arith-op + (eval l env) (eval r env))]
    [(Sub l r) (arith-op - (eval l env) (eval r env))]
    [(Mul l r) (arith-op * (eval l env) (eval r env))]
    [(Div l r) (arith-op / (eval l env) (eval r env))]
    [(With bound-id named-expr bound-body)
    (eval bound-body
          (Extend bound-id (eval named-expr env) env))]
    [(WRec bound-id named-expr bound-body)
    (eval bound-body
          (extend-rec bound-id named-expr env))]
    [(Id name) (lookup name env)]
    [(Fun bound-id bound-body)
    (FunV bound-id bound-body env)]
    [(Call fun-expr arg-expr)
    (let ([fval (eval fun-expr env)])
      (cases fval
        [(FunV bound-id bound-body f-env)
          (eval bound-body
                (Extend bound-id (eval arg-expr env) f-env))]
        [else (error 'eval "`call' expects a function, got: ~s"
                            fval)]))]))

(: run : String -> Number)
;; evaluate a FLANG program contained in a string
(define (run str)
  (let ([result (eval (parse str) (EmptyEnv))])
    (cases result
      [(NumV n) n]
      [else (error 'run "evaluation returned a non-number: ~s"
                  result)])))

;; tests
(test (run "{call {fun {x} {+ x 1}} 4}")
      => 5)
(test (run "{with {add3 {fun {x} {+ x 3}}}
              {call add3 1}}")
      => 4)
(test (run "{with {add3 {fun {x} {+ x 3}}}
              {with {add1 {fun {x} {+ x 1}}}
                {with {x 3}
                  {call add1 {call add3 x}}}}}")
      => 7)
(test (run "{with {identity {fun {x} x}}
              {with {foo {fun {x} {+ x 1}}}
                {call {call identity foo} 123}}}")
      => 124)
(test (run "{with {x 3}
              {with {f {fun {y} {+ x y}}}
                {with {x 5}
                  {call f 4}}}}")
      => 7)
(test (run "{call {with {x 3}
                    {fun {y} {+ x y}}}
                  4}")
      => 7)
(test (run "{with {f {with {x 3} {fun {y} {+ x y}}}}
              {with {x 100}
                {call f 4}}}")
      => 7)
(test (run "{call {call {fun {x} {call x 1}}
                        {fun {x} {fun {y} {+ x y}}}}
                  123}")
      => 124)

Implementing rec Using Cyclic StructuresTuesday, October 23rd

PLAI §10

Looking at the arrows in the environment diagrams, what we’re really looking for is a closure that has an environment pointer which is the same environment in which it was defined. This will make it possible for fact to be bound to a closure that can refer to itself since its environment is the same one in which it is defined. However, so far we have no tools that makes it possible to do this.

What we need is to create a “cycle of pointers”, and so far we do not have a way of achieving that: when we create a closure, we begin with an environment which is saved in the slot’s environment slot, but we want that closure to be the value of a binding in that same environment.

Boxes and MutationTuesday, October 23rd

To actually implement a circular structure, we will now use side-effects, using a new kind of Racket value which supports mutation: a box. A box value is built with the box constructor:

(define my-thing (box 7))

the value is retrieved with the `unbox’ function,

(* 6 (unbox my-thing))

and finally, the value can be changed with the set-box! function.

(set-box! my-thing 17)
(* 6 (unbox my-thing))

An important thing to note is that set-box! is much like display etc, it returns a value that is not printed in the Racket REPL, because there is no point in using the result of a set-box!, it is called for the side-effect it generates. (Languages like C blur this distinction between returning a value and a side-effect with its assignment statement.)

As a side note, we now have side effects of two kinds: mutation of state, and I/O (at least the O part). (Actually, there is also infinite looping that can be viewed as another form of a side effect.) This means that we’re now in a completely different world, and lots of new things can make sense now. A few things that you should know about:

When any one of these things is used (in Racket or other languages), you can tell that side-effects are involved, because there is no point in any of them otherwise. In addition, any name that ends with a ! (“bang”) is used to mark a function that changes state (usually a function that only changes state).

So how do we create a cycle? Simple, boxes can have any value, and they can be put in other values like lists, so we can do this:

#lang pl untyped
(define foo (list 1 (box 3)))
(set-box! (second foo) foo)

and we get a circular value. (Note how it is printed.) And with types:

#lang pl
(: foo : (List Number (Boxof Any)))
(define foo (list 1 (box 3)))
(set-box! (second foo) foo)

Types for BoxesTuesday, October 30th

Obviously, Any is not too great — it is the most generic type, so it provides the least information. For example, notice that

(unbox (second foo))

returns the right list, which is equal to foo itself — but if we try to grab some part of the resulting list:

(second (unbox (second foo)))

we get a type error, because the result of the unbox is Any, so Typed Racket knows nothing about it, and won’t allow you to treat it as a list. It is not too surprising that the type constructor that can help in this case is Rec which we have already seen — it allows a type that can refer to itself:

#lang pl
(: foo : (Rec this (List Number (Boxof (U #f this)))))
(define foo (list 1 (box #f)))
(set-box! (second foo) foo)

Note that either foo or the value in the box are both printed with a Rec type — the value in the box can’t just have a (U #f this) type, since this doesn’t mean anything in there, so the whole type needs to still be present.

There is another issue to be aware of with Boxof types. For most type constructors (like Listof), if T1 is a subtype of T2, then we also know that(Listof T1) is a subtype of (Listof T2). This makes the following code typecheck:

#lang pl
(: foo : (Listof Number) -> Number)
(define (foo l)
  (first l))
(: bar : Integer -> Number)
(define (bar x)
  (foo (list x)))

Since the (Listof Integer) is a subtype of the (Listof Number) input for foo, the application typechecks. But this is not the same for the output type, for example — if we change the bar type to:

(: bar : Integer -> Integer)

we get a type error since Number is not a subtype of Integer. So subtypes are required to “go up” on the input side and “down” on the other. So, in a sense, the fact that boxes are mutable means that their contents can be considered to be on the other side of the arrow, which is why for such T1 subtype of T2, it is (Boxof T2) that is a subtype of (Boxof T1), instead of the usual. For example, this doesn’t work:

#lang pl
(: foo : (Boxof Number) -> Number)
(define (foo b)
  (unbox b))
(: bar : Integer -> Number)
(define (bar x)
  (: b : (Boxof Integer))
  (define b (box x))
  (foo b))

And you can see why this is the case — the marked line is fine given a Number contents, so if the type checker allows passing in a box holding an integer, then that expression would mutate the contents and make it an invalid value.

However, boxes are not only mutable, they hold a value that can be read too, which means that they’re on both sides of the arrow, and this means that (Boxof T1) is a subtype of (Boxof T2) if T2 is a subtype of T1 and T1 is a subtype of T2 — in other words, this happens only when T1 and T2 are the same type. (See below for an extended demonstration of all of this.)

Note also that this demonstration requires that extra b definition, if it’s skipped:

(define (bar x)
  (foo (box x)))

then this will typecheck again — Typed Racket will just consider the context that requires a box holding a Number, and it is still fine to initialize such a box with an Integer value.

As a side comment, this didn’t always work. Earlier in its existence, Typed Racket would always choose a specific type for values, which would lead to confusing errors with boxes. For example, the above would need to be written as

(define (bar x)
  (foo (box (ann x : Number))))

to prevent Typed Racket from inferring a specific type. This is no longer the case, but there can still be some surprises. A similar annotation was needed in the case of a list holding a self-referential box, to avoid the initial #f from getting a specific-but-wrong type.

Boxof’s Lack of SubtypingTuesday, October 30th

The lack of any subtype relations between (Boxof T) and (Boxof S) regardless of S and T can roughly be explained as follows.

First, a box is a container that you can pull a value out of — which makes it similar to lists. In the case of lists, we have:

if:          S  subtype-of          T
then: (Listof S)  subtype-of  (Listof T)

This is true for all such containers that you can pull a value out of: if you expect to pull a T but you’re given a container of a subtype S, then things are still fine. Such “containers” include functions that produce a value — for example:

if:        S  subtype-of      T
then:  Q -> S  subtype-of  Q -> T

However, functions also have the other side, where things are different — instead of a side of some produced value, it’s the side of the consumed value. We get the opposite rule there:

if:    T      subtype-of  S
then:  S -> Q  subtype-of  T -> Q

To see why this is right, use Number and Integer for S and T:

if:    Integer      subtype-of  Number
then:  Number -> Q  subtype-of  Integer -> Q

so — if you expect a function that takes a number is a subtype of one that takes an integer; in other words, every function that takes a number is also a function that takes an integer, but not the other way.

To summarize all of this, when you make the output type of a function “smaller” (more constrained), the resulting type is smaller, but on the input side things are flipped — a bigger input type means a more constrained function.

Now, a (Boxof T) is a producer of T when you pull a value out of the box, but it’s also a consumer of T when you put such a value in it. This means that — using the above analogy — the T is on both sides of the arrow. This means that

if:    S subtype-of T  *and*  T subtype-of S
then:  (Boxof S) subtype-of (Boxof T)

which is actually:

if:          S  is-the-same-type-as        T
then:  (Boxof S)  is-the-same-type-as  (Boxof T)

A different way to look at this conclusion is to consider the function type of (A -> A): when is it a subtype of some other (B -> B)? Only when A is a subtype of B and B is a subtype of A, which means that this happens only when A and B are the same type.

(Side note: this is related to the fact that in logic, P => Q is roughly equivalent to not(P) or Q — the left side, P, is inside a negation. It also explains why in ((S -> T) -> Q) the S obeys the first rule, as if it was on the right side — because it’s negated twice.)

The following piece of code makes the analogy to function types more formally. Boxes behave as if their contents is on both sides of a function arrow — on the right because they’re readable, and on the left because they’re writable, which the conclusion that a (Boxof A) type is a subtype of itself and no other (Boxof B).

#lang pl

;; a type for a "read-only" box
(define-type (Boxof/R A) = (-> A))
;; Boxof/R constructor
(: box/r : (All (A) A -> (Boxof/R A)))
(define (box/r x) (lambda () x))
;; we can see that (Boxof/R T1) is a subtype of (Boxof/R T2)
;; if T1 is a subtype of T2 (this is not surprising, since
;; these boxes are similar to any other container, like lists):
(: foo1 : Integer -> (Boxof/R Integer))
(define (foo1 b) (box/r b))
(: bar1 : (Boxof/R Number) -> Number)
(define (bar1 b) (b))
(test (bar1 (foo1 123)) => 123)

;; a type for a "write-only" box
(define-type (Boxof/W A) = (A -> Void))
;; Boxof/W constructor
(: box/w : (All (A) A -> (Boxof/W A)))
(define (box/w x) (lambda (new) (set! x new)))
;; in contrast to the above, (Boxof/W T1) is a subtype of
;; (Boxof/W T2) if T2 is a subtype of T1, *not* the other way
;; (and note how this is related to A being on the *left* side
;; of the arrow in the `Boxof/W' type):
(: foo2 : Number -> (Boxof/W Number))
(define (foo2 b) (box/w b))
(: bar2 : (Boxof/W Integer) Integer -> Void)
(define (bar2 b new) (b new))
(test (bar2 (foo2 123) 456))

;; combining the above two into a type for a "read/write" box
(define-type (Boxof/RW A) = (A -> A))
;; Boxof/RW constructor
(: box/rw : (All (A) A -> (Boxof/RW A)))
(define (box/rw x) (lambda (new) (let ([old x]) (set! x new) old)))
;; this combines the above two: `A' appears on both sides of the
;; arrow, so (Boxof/RW T1) is a subtype of (Boxof/RW T2) if T1
;; is a subtype of T2 (because there's an A on the right) *and*
;; if T2 is a subtype of T1 (because there's another A on the
;; left) -- and that can happen only when T1 and T2 are the same
;; type.  So this is a type error:
;;  (: foo3 : Integer -> (Boxof/RW Integer))
;;  (define (foo3 b) (box/rw b))
;;  (: bar3 : (Boxof/RW Number) Number -> Number)
;;  (define (bar3 b new) (b new))
;;  (test (bar3 (foo3 123) 456) => 123)
;;  ** Expected (Number -> Number), but got (Integer -> Integer)
;; And this a type error too:
;;  (: foo3 : Number -> (Boxof/RW Number))
;;  (define (foo3 b) (box/rw b))
;;  (: bar3 : (Boxof/RW Integer) Integer -> Integer)
;;  (define (bar3 b new) (b new))
;;  (test (bar3 (foo3 123) 456) => 123)
;;  ** Expected (Integer -> Integer), but got (Number -> Number)
;; The two types must be the same for this to work:
(: foo3 : Integer -> (Boxof/RW Integer))
(define (foo3 b) (box/rw b))
(: bar3 : (Boxof/RW Integer) Integer -> Integer)
(define (bar3 b new) (b new))
(test (bar3 (foo3 123) 456) => 123)

Implementing a Circular EnvironmentTuesday, October 30th

We now use this to implement rec in the following way:

  1. Change environments so that instead of values they hold boxes of values: (Boxof VAL) instead of VAL, and whenever lookup is used, the resulting boxed value is unboxed,

  2. In the WRec case, create the new environment with some temporary binding for the identifier — any value will do since it should not be used (when named expressions are always fun expressions),

  3. Evaluate the expression in the new environment,

  4. Change the binding of the identifier (the box) to the result of this evaluation.

The resulting definition is:

(: extend-rec : Symbol FLANG ENV -> ENV)
;; extend an environment with a new binding that is the result of
;; evaluating an expression in the same environment as the extended
;; result
(define (extend-rec id expr rest-env)
  (let ([new-cell (box (NumV 42))])
    (let ([new-env (Extend id new-cell rest-env)])
      (let ([value (eval expr new-env)])
        (set-box! new-cell value)
        new-env))))

Racket has another let relative for such cases of multiple-nested lets — let*. This form is a derived form — it is defined as a shorthand for using nested lets. The above is therefore exactly the same as this code:

(: extend-rec : Symbol FLANG ENV -> ENV)
;; extend an environment with a new binding that is the result of
;; evaluating an expression in the same environment as the extended
;; result
(define (extend-rec id expr rest-env)
  (let* ([new-cell (box (NumV 42))]
        [new-env  (Extend id new-cell rest-env)]
        [value    (eval expr new-env)])
    (set-box! new-cell value)
    new-env))

This let* form can be read almost as a C/Java-ish kind of code:

fun extend_rec(id, expr, rest_env) {
  new_cell  = new NumV(42);
  new_env  = Extend(id, new_cell, rest_env);
  value    = eval(expr, new_env);
  *new_cell = value;
  return new_env;
}

The code can be simpler if we fold the evaluation into the set-box! (since value is used just there), and if use lookup to do the mutation — since this way there is no need to hold onto the box. This is a bit more expensive, but since the binding is guaranteed to be the first one in the environment, the addition is just one quick step. The only binding that we need is the one for the new environment, which we can do as an internal definition, leaving us with:

(: extend-rec : Symbol FLANG ENV -> ENV)
(define (extend-rec id expr rest-env)
  (define new-env (Extend id (box (NumV 42)) rest-env))
  (set-box! (lookup id new-env) (eval expr new-env))
  new-env)

A complete rehacked version of FLANG with a rec binding follows:

#lang pl

(define-type FLANG
  [Num  Number]
  [Add  FLANG FLANG]
  [Sub  FLANG FLANG]
  [Mul  FLANG FLANG]
  [Div  FLANG FLANG]
  [Id  Symbol]
  [With Symbol FLANG FLANG]
  [WRec Symbol FLANG FLANG]
  [Fun  Symbol FLANG]
  [Call FLANG FLANG])

(: parse-sexpr : Sexpr -> FLANG)
;; parses s-expressions into FLANGs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(cons (or 'with 'rec) more)
    (match sexpr
      [(list 'with (list (symbol: name) named) body)
        (With name (parse-sexpr named) (parse-sexpr body))]
      [(list 'rec (list (symbol: name) named) body)
        (WRec name (parse-sexpr named) (parse-sexpr body))]
      [(cons x more)
        (error 'parse-sexpr "bad `~s' syntax in ~s" x sexpr)])]
    [(cons 'fun more)
    (match sexpr
      [(list 'fun (list (symbol: name)) body)
        (Fun name (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `fun' syntax in ~s" sexpr)])]
    [(list '+ lhs rhs) (Add (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '- lhs rhs) (Sub (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '* lhs rhs) (Mul (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '/ lhs rhs) (Div (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list 'call fun arg)
                      (Call (parse-sexpr fun) (parse-sexpr arg))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

(: parse : String -> FLANG)
;; parses a string containing a FLANG expression to a FLANG AST
(define (parse str)
  (parse-sexpr (string->sexpr str)))

;; Types for environments, values, and a lookup function

(define-type ENV
  [EmptyEnv]
  [Extend Symbol (Boxof VAL) ENV])

(define-type VAL
  [NumV Number]
  [FunV Symbol FLANG ENV])

(: lookup : Symbol ENV -> (Boxof VAL))
;; lookup a symbol in an environment, return its value or throw an
;; error if it isn't bound
(define (lookup name env)
  (cases env
    [(EmptyEnv) (error 'lookup "no binding for ~s" name)]
    [(Extend id boxed-val rest-env)
    (if (eq? id name) boxed-val (lookup name rest-env))]))

(: extend-rec : Symbol FLANG ENV -> ENV)
;; extend an environment with a new binding that is the result of
;; evaluating an expression in the same environment as the extended
;; result
(define (extend-rec id expr rest-env)
  (define new-env (Extend id (box (NumV 42)) rest-env))
  (set-box! (lookup id new-env) (eval expr new-env))
  new-env)

(: NumV->number : VAL -> Number)
;; convert a FLANG runtime numeric value to a Racket one
(define (NumV->number val)
  (cases val
    [(NumV n) n]
    [else (error 'arith-op "expected a number, got: ~s" val)]))

(: arith-op : (Number Number -> Number) VAL VAL -> VAL)
;; gets a Racket numeric binary operator, and uses it within a NumV
;; wrapper
(define (arith-op op val1 val2)
  (NumV (op (NumV->number val1) (NumV->number val2))))

(: eval : FLANG ENV -> VAL)
;; evaluates FLANG expressions by reducing them to values
(define (eval expr env)
  (cases expr
    [(Num n) (NumV n)]
    [(Add l r) (arith-op + (eval l env) (eval r env))]
    [(Sub l r) (arith-op - (eval l env) (eval r env))]
    [(Mul l r) (arith-op * (eval l env) (eval r env))]
    [(Div l r) (arith-op / (eval l env) (eval r env))]
    [(With bound-id named-expr bound-body)
    (eval bound-body
          (Extend bound-id (box (eval named-expr env)) env))]
    [(WRec bound-id named-expr bound-body)
    (eval bound-body
          (extend-rec bound-id named-expr env))]
    [(Id name) (unbox (lookup name env))]
    [(Fun bound-id bound-body)
    (FunV bound-id bound-body env)]
    [(Call fun-expr arg-expr)
    (let ([fval (eval fun-expr env)])
      (cases fval
        [(FunV bound-id bound-body f-env)
          (eval bound-body
                (Extend bound-id (box (eval arg-expr env)) f-env))]
        [else (error 'eval "`call' expects a function, got: ~s"
                            fval)]))]))

(: run : String -> Number)
;; evaluate a FLANG program contained in a string
(define (run str)
  (let ([result (eval (parse str) (EmptyEnv))])
    (cases result
      [(NumV n) n]
      [else (error 'run "evaluation returned a non-number: ~s"
                  result)])))

;; tests
(test (run "{call {fun {x} {+ x 1}} 4}")
      => 5)
(test (run "{with {add3 {fun {x} {+ x 3}}}
              {call add3 1}}")
      => 4)
(test (run "{with {add3 {fun {x} {+ x 3}}}
              {with {add1 {fun {x} {+ x 1}}}
                {with {x 3}
                  {call add1 {call add3 x}}}}}")
      => 7)
(test (run "{with {identity {fun {x} x}}
              {with {foo {fun {x} {+ x 1}}}
                {call {call identity foo} 123}}}")
      => 124)
(test (run "{with {x 3}
              {with {f {fun {y} {+ x y}}}
                {with {x 5}
                  {call f 4}}}}")
      => 7)
(test (run "{call {with {x 3}
                    {fun {y} {+ x y}}}
                  4}")
      => 7)
(test (run "{with {f {with {x 3} {fun {y} {+ x y}}}}
              {with {x 100}
                {call f 4}}}")
      => 7)
(test (run "{call {call {fun {x} {call x 1}}
                        {fun {x} {fun {y} {+ x y}}}}
                  123}")
      => 124)

Variable MutationTuesday, October 30th

PLAI §12 and PLAI §13 (different: adds boxes to the language)

PLAI §14 (that’s what we do)

The code that we now have implements recursion by changing bindings, and to make that possible we made environments hold boxes for all bindings, therefore bindings are all mutable now. We can use this to add more functionality to our evaluator, by allowing changing any variable — we can add a set! form:

{set! <id> <FLANG>}

to the evaluator that will modify the value of a variable. To implement this functionality, all we need to do is to use lookup to retrieve some box, then evaluate the expression and put the result in that box. The actual implementation is left as a homework exercise.

One thing that should be considered here is — all of the expressions in our language evaluate to some value, the question is what should be the value of a set! expression? There are three obvious choices:

  1. return some bogus value,

  2. return the value that was assigned,

  3. return the value that was previously in the box.

Each one of these has its own advantage — for example, C uses the second option to chain assignments (eg, x = y = 0) and to allow side effects where an expression is expected (eg, while (x = x-1) ...).

The third one is useful in cases where you might use the old value that is overwritten — for example, if C had this behavior, you could pop a value from a linked list using something like:

first(stack = rest(stack));

because the argument to first will be the old value of stack, before it changed to be its rest. You could also swap two variables in a single expression: x = y = x.

(Note that the expression x = x + 1 has the meaning of C’s ++x when option (2) is used, and x++ when option (3) is used.)

Racket chooses the first option, and we will do the same in our language. The advantage here is that you get no discounts, therefore you must be explicit about what values you want to return in situations where there is no obvious choice. This leads to more robust programs since you do not get other programmers that will rely on a feature of your code that you did not plan on.

In any case, the modification that introduces mutation is small, but it has a tremendous effect on our language: it was true for Racket, and it is true for FLANG. We have seen how mutation affects the language subset that we use, and in the extension of our FLANG the effect is even stronger: since any variable can change (no need for explicit boxes). In other words, a binding is not always the same — in can change as a result of a set! expression. Of course, we could extend our language with boxes (using Racket boxes to implement FLANG boxes), but that will be a little more verbose.

Note that Racket does have a set! form, and in addition, fields in structs can be made modifiable. However, we do not use any of these. At least not for now.

State and EnvironmentsTuesday, October 30th

A quick example of how mutation can be used:

(define counter
  (let ([counter (box 0)])
    (lambda ()
      (set-box! counter (+ 1 (unbox counter)))
      (unbox counter))))

and compare that to:

(define (make-counter)
  (let ([counter (box 0)])
    (lambda ()
      (set-box! counter (+ 1 (unbox counter)))
      (unbox counter))))

It is a good idea if you follow the exact evaluation of

(define foo (make-counter))
(define bar (make-counter))

and see how both bindings have separate environment so each one gets its own private state. The equivalent code in the homework interpreter extended with set! doesn’t need boxes:

{with {make-counter
        {fun {}
          {with {counter 0}
            {fun {}
              {set! counter {+ counter 1}}
              counter}}}}
  {with {foo {call make-counter}}
    {with {bar {call make-counter}}
      ...}}}

(To see multiple values from a single expression you can extend the language with a list binding.) Note that we cannot describe this behavior with substitution rules! We now use the environments to make it possible to change bindings — so finally an environment is actually an environment rather than a substitution cache.

When you look at the above, note that we still use lexical scope — in fact, the local binding is actually a private state that nobody can access. For example, if we write this:

(define counter
  (let ([counter (box 0)])
    (lambda ()
      (set-box! counter (+ 1 (unbox counter)))
      (if (zero? (modulo (unbox counter) 4)) 'tock 'tick))))

then the resulting function that us bound to counter keeps a local integer state which no other code can access — you cannot modify it, reset it, or even know if it is really an integer that is used in there.

Implementing Objects with StateTuesday, October 30th

We have already seen how several pieces of information can be encapsulate in a Racket closure that keeps them all; now we can do a little more — we can actually have mutable state, which leads to a natural way to implement objects. For example:

(define (make-point x y)
  (let ([xb (box x)]
        [yb (box y)])
    (lambda (msg)
      (match msg
        ['getx (unbox xb)]
        ['gety (unbox yb)]
        ['incx (set-box! xb (add1 (unbox xb)))]))))

implements a constructor for point objects which keep two values and can move one of them. Note that the messages act as a form of methods, and that the values themselves are hidden and are accessible only through the interface that these messages make. For example, if these points correspond to some graphic object on the screen, we can easily incorporate a necessary screen update:

(define (make-point x y)
  (let ([xb (box x)]
        [yb (box y)])
    (lambda (msg)
      (match msg
        ['getx (unbox xb)]
        ['gety (unbox yb)]
        ['incx (set-box! xb (add1 (unbox xb)))
              (update-screen)]))))

and be sure that this is always done when the value changes — since there is no way to change the value except through this interface.

A more complete example would define functions that actually send these messages — here is a better implementation of a point object and the corresponding accessors and mutators:

(define (make-point x y)
  (let ([xb (box x)]
        [yb (box y)])
    (lambda (msg)
      (match msg
        ['getx (unbox xb)]
        ['gety (unbox yb)]
        [(list 'setx newx)
        (set-box! xb newx)
        (update-screen)]
        [(list 'sety newy)
        (set-box! yb newy)
        (update-screen)]))))
(define (point-x p) (p 'getx))
(define (point-y p) (p 'gety))
(define (set-point-x! p x) (p (list 'setx x)))
(define (set-point-y! p y) (p (list 'sety y)))

And a quick imitation of inheritance can be achieved using delegation to an instance of the super-class:

(define (make-colored-point x y color)
  (let ([p (make-point x y)])
    (lambda (msg)
      (match msg
        ['getcolor color]
        [else (p msg)]))))

You can see how all of these could come from some preprocessing of a more normal-looking class definition form, like:

(defclass point (x y)
  (public (getx) x)
  (public (gety) y)
  (public (setx new) (set! x newx))
  (public (setx new) (set! x newx)))

(defclass colored-point point (c)
  (public (getcolor) c))

The Toy LanguageTuesday, October 30th

Not in PLAI

A quick note: from now on, we will work with a variation of our language — it will change the syntax to look a little more like Racket, and we will use Racket values for values in our language and Racket functions for built-ins in our language.

Main highlights:

The following is the complete implementation.

#lang pl

;;; ----------------------------------------------------------------
;;; Syntax

#| The BNF:
  <TOY> ::= <num>
          | <id>
          | { bind {{ <id> <TOY> } ... } <TOY> }
          | { fun { <id> ... } <TOY> }
          | { if <TOY> <TOY> <TOY> }
          | { <TOY> <TOY> ... }
|#

;; A matching abstract syntax tree datatype:
(define-type TOY
  [Num  Number]
  [Id  Symbol]
  [Bind (Listof Symbol) (Listof TOY) TOY]
  [Fun  (Listof Symbol) TOY]
  [Call TOY (Listof TOY)]
  [If  TOY TOY TOY])

(: unique-list? : (Listof Any) -> Boolean)
;; Tests whether a list is unique, guards Bind and Fun values.
(define (unique-list? xs)
  (or (null? xs)
      (and (not (member (first xs) (rest xs)))
          (unique-list? (rest xs)))))

(: parse-sexpr : Sexpr -> TOY)
;; parses s-expressions into TOYs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(cons 'bind more)
    (match sexpr
      [(list 'bind (list (list (symbol: names) (sexpr: nameds))
                          ...)
          body)
        (if (unique-list? names)
          (Bind names (map parse-sexpr nameds) (parse-sexpr body))
          (error 'parse-sexpr "duplicate `bind' names: ~s" names))]
      [else (error 'parse-sexpr "bad `bind' syntax in ~s" sexpr)])]
    [(cons 'fun more)
    (match sexpr
      [(list 'fun (list (symbol: names) ...) body)
        (if (unique-list? names)
          (Fun names (parse-sexpr body))
          (error 'parse-sexpr "duplicate `fun' names: ~s" names))]
      [else (error 'parse-sexpr "bad `fun' syntax in ~s" sexpr)])]
    [(cons 'if more)
    (match sexpr
      [(list 'if cond then else)
        (If (parse-sexpr cond)
            (parse-sexpr then)
            (parse-sexpr else))]
      [else (error 'parse-sexpr "bad `if' syntax in ~s" sexpr)])]
    [(list fun args ...) ; other lists are applications
    (Call (parse-sexpr fun)
          (map parse-sexpr args))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

(: parse : String -> TOY)
;; Parses a string containing an TOY expression to a TOY AST.
(define (parse str)
  (parse-sexpr (string->sexpr str)))

;;; ----------------------------------------------------------------
;;; Values and environments

(define-type ENV
  [EmptyEnv]
  [FrameEnv FRAME ENV])

;; a frame is an association list of names and values.
(define-type FRAME = (Listof (List Symbol VAL)))

(define-type VAL
  [RktV  Any]
  [FunV  (Listof Symbol) TOY ENV]
  [PrimV ((Listof VAL) -> VAL)])

(: extend : (Listof Symbol) (Listof VAL) ENV -> ENV)
;; extends an environment with a new frame.
(define (extend names values env)
  (if (= (length names) (length values))
    (FrameEnv (map (lambda ([name : Symbol] [val : VAL])
                    (list name val))
                  names values)
              env)
    (error 'extend "arity mismatch for names: ~s" names)))

(: lookup : Symbol ENV -> VAL)
;; lookup a symbol in an environment, frame by frame,
;; return its value or throw an error if it isn't bound
(define (lookup name env)
  (cases env
    [(EmptyEnv) (error 'lookup "no binding for ~s" name)]
    [(FrameEnv frame rest)
    (let ([cell (assq name frame)])
      (if cell
        (second cell)
        (lookup name rest)))]))

(: unwrap-rktv : VAL -> Any)
;; helper for `racket-func->prim-val': unwrap a RktV wrapper in
;; preparation to be sent to the primitive function
(define (unwrap-rktv x)
  (cases x
    [(RktV v) v]
    [else (error 'racket-func "bad input: ~s" x)]))

(: racket-func->prim-val : Function -> VAL)
;; converts a racket function to a primitive evaluator function
;; which is a PrimV holding a ((Listof VAL) -> VAL) function.
;; (the resulting function will use the list function as is,
;; and it is the list function's responsibility to throw an error
;; if it's given a bad number of arguments or bad input types.)
(define (racket-func->prim-val racket-func)
  (define list-func (make-untyped-list-function racket-func))
  (PrimV (lambda (args)
          (RktV (list-func (map unwrap-rktv args))))))

;; The global environment has a few primitives:
(: global-environment : ENV)
(define global-environment
  (FrameEnv (list (list '+ (racket-func->prim-val +))
                  (list '- (racket-func->prim-val -))
                  (list '* (racket-func->prim-val *))
                  (list '/ (racket-func->prim-val /))
                  (list '< (racket-func->prim-val <))
                  (list '> (racket-func->prim-val >))
                  (list '= (racket-func->prim-val =))
                  ;; values
                  (list 'true  (RktV #t))
                  (list 'false (RktV #f)))
            (EmptyEnv)))

;;; ----------------------------------------------------------------
;;; Evaluation

(: eval : TOY ENV -> VAL)
;; evaluates TOY expressions.
(define (eval expr env)
  ;; convenient helper
  (: eval* : TOY -> VAL)
  (define (eval* expr) (eval expr env))
  (cases expr
    [(Num n)  (RktV n)]
    [(Id name) (lookup name env)]
    [(Bind names exprs bound-body)
    (eval bound-body (extend names (map eval* exprs) env))]
    [(Fun names bound-body)
    (FunV names bound-body env)]
    [(Call fun-expr arg-exprs)
    (let ([fval (eval* fun-expr)]
          [arg-vals (map eval* arg-exprs)])
      (cases fval
        [(PrimV proc) (proc arg-vals)]
        [(FunV names body fun-env)
          (eval body (extend names arg-vals fun-env))]
        [else (error 'eval "function call with a non-function: ~s"
                      fval)]))]
    [(If cond-expr then-expr else-expr)
    (eval* (if (cases (eval* cond-expr)
                  [(RktV v) v] ; Racket value => use as boolean
                  [else #t])  ; other values are always true
              then-expr
              else-expr))]))

(: run : String -> Any)
;; evaluate a TOY program contained in a string
(define (run str)
  (let ([result (eval (parse str) global-environment)])
    (cases result
      [(RktV v) v]
      [else (error 'run "evaluation returned a bad value: ~s"
                  result)])))

;;; ----------------------------------------------------------------
;;; Tests

(test (run "{{fun {x} {+ x 1}} 4}")
      => 5)
(test (run "{bind {{add3 {fun {x} {+ x 3}}}} {add3 1}}")
      => 4)
(test (run "{bind {{add3 {fun {x} {+ x 3}}}
                  {add1 {fun {x} {+ x 1}}}}
              {bind {{x 3}} {add1 {add3 x}}}}")
      => 7)
(test (run "{bind {{identity {fun {x} x}}
                  {foo {fun {x} {+ x 1}}}}
              {{identity foo} 123}}")
      => 124)
(test (run "{bind {{x 3}}
              {bind {{f {fun {y} {+ x y}}}}
                {bind {{x 5}}
                  {f 4}}}}")
      => 7)
(test (run "{{{fun {x} {x 1}}
              {fun {x} {fun {y} {+ x y}}}}
            123}")
      => 124)

;; More tests for complete coverage
(test (run "{bind x 5 x}")      =error> "bad `bind' syntax")
(test (run "{fun x x}")        =error> "bad `fun' syntax")
(test (run "{if x}")            =error> "bad `if' syntax")
(test (run "{}")                =error> "bad syntax")
(test (run "{bind {{x 5} {x 5}} x}") =error> "duplicate*bind*names")
(test (run "{fun {x x} x}")    =error> "duplicate*fun*names")
(test (run "{+ x 1}")          =error> "no binding for")
(test (run "{+ 1 {fun {x} x}}") =error> "bad input")
(test (run "{+ 1 {fun {x} x}}") =error> "bad input")
(test (run "{1 2}")            =error> "with a non-function")
(test (run "{{fun {x} x}}")    =error> "arity mismatch")
(test (run "{if {< 4 5} 6 7}")  => 6)
(test (run "{if {< 5 4} 6 7}")  => 7)
(test (run "{if + 6 7}")        => 6)
(test (run "{fun {x} x}")      =error> "returned a bad value")

;;; ----------------------------------------------------------------

Compilation and Partial EvaluationTuesday, November 6th

Instead of interpreting an expression, which is performing a full evaluation, we can think about compiling it: translating it to a different language which we can later run more easily, more efficiently, on more platforms, etc. Another feature that is usually associated with compilation is that a lot more work was done at the compilation stage, making the actual running of the code faster.

For example, translating an AST into one that has de-Bruijn indexes instead of identifier names is a form of compilation — not only is it translating one language into another, it does the work involved in name lookup before the program starts running.

This is something that we can experiment with now. An easy way to achieve this is to start with our evaluation function:

(: eval : TOY ENV -> VAL)
;; evaluates TOY expressions.
(define (eval expr env)
  ;; convenient helper
  (: eval* : TOY -> VAL)
  (define (eval* expr) (eval expr env))
  (cases expr
    [(Num n)  (RktV n)]
    [(Id name) (lookup name env)]
    [(Bind names exprs bound-body)
    (eval bound-body (extend names (map eval* exprs) env))]
    [(Fun names bound-body)
    (FunV names bound-body env)]
    [(Call fun-expr arg-exprs)
    (let ([fval (eval* fun-expr)]
          [arg-vals (map eval* arg-exprs)])
      (cases fval
        [(PrimV proc) (proc arg-vals)]
        [(FunV names body fun-env)
          (eval body (extend names arg-vals fun-env))]
        [else (error 'eval "function call with a non-function: ~s"
                      fval)]))]
    [(If cond-expr then-expr else-expr)
    (eval* (if (cases (eval* cond-expr)
                  [(RktV v) v] ; Racket value => use as boolean
                  [else #t])  ; other values are always true
              then-expr
              else-expr))]))

and change it so it compiles a given expression to a Racket function. (This is, of course, just to demonstrate a conceptual point, it is only the tip of what compilers actually do…) This means that we need to turn it into a function that receives a TOY expression and compiles it. In other words, eval no longer consumes and environment argument which makes sense because the environment is a place to hold run-time values, so it is a data structure that is not part of the compiler (it is usually represented as the call stack).

So we split the two arguments into a compile-time and run-time, which can be done by simply currying the eval function — here this is done, and all calls to eval are also curried:

(: eval : TOY -> ENV -> VAL) ;*** note the curried type
;; evaluates TOY expressions.
(define (eval expr)
  (lambda (env)
    ;; convenient helper
    (: eval* : TOY -> VAL)
    (define (eval* expr) ((eval expr) env))
    (cases expr
      [(Num n)  (RktV n)]
      [(Id name) (lookup name env)]
      [(Bind names exprs bound-body)
      ((eval bound-body) (extend names (map eval* exprs) env))]
      [(Fun names bound-body)
      (FunV names bound-body env)]
      [(Call fun-expr arg-exprs)
      (let ([fval (eval* fun-expr)]
            [arg-vals (map eval* arg-exprs)])
        (cases fval
          [(PrimV proc) (proc arg-vals)]
          [(FunV names body fun-env)
            ((eval body) (extend names arg-vals fun-env))]
          [else (error 'eval
                        "function call with a non-function: ~s"
                        fval)]))]
      [(If cond-expr then-expr else-expr)
      (eval* (if (cases (eval* cond-expr)
                    [(RktV v) v] ; Racket value => use as boolean
                    [else #t])  ; other values are always true
                then-expr
                else-expr))])))

We also need to change the eval call in the main run function:

(: run : String -> Any)
;; evaluate a TOY program contained in a string
(define (run str)
  (let ([result ((eval (parse str)) global-environment)])
    (cases result
      [(RktV v) v]
      [else (error 'run "evaluation returned a bad value: ~s"
                  result)])))

Not much has changed so far.

Note that in the general case of a compiler we need to run a program several times, so we’d want to avoid parsing it over and over again. We can do that by keeping a single parsed AST of the input. Now we went one step further by making it possible to do more work ahead and keep the result of the first “stage” of eval around (except that “more work” is really not saying much at the moment):

(: run : String -> Any)
;; evaluate a TOY program contained in a string
(define (run str)
  (let* ([compiled (eval (parse str))]
        [result  (compiled global-environment)])
    (cases result
      [(RktV v) v]
      [else (error 'run "evaluation returned a bad value: ~s"
                  result)])))

At this point, even though our “compiler” is not much more than a slightly different representation of the same functionality, we rename eval to compile which is a more appropriate description of what we intend it to do (so we change the purpose statement too):

(: compile : TOY -> ENV -> VAL)
;; compiles TOY expressions to Racket functions.
(define (compile expr)
  (lambda (env)
    (: compile* : TOY -> VAL)
    (define (compile* expr) ((compile expr) env))
    (cases expr
      [(Num n)  (RktV n)]
      [(Id name) (lookup name env)]
      [(Bind names exprs bound-body)
      ((compile bound-body)
        (extend names (map compile* exprs) env))]
      [(Fun names bound-body)
      (FunV names bound-body env)]
      [(Call fun-expr arg-exprs)
      (let ([fval (compile* fun-expr)]
            [arg-vals (map compile* arg-exprs)])
        (cases fval
          [(PrimV proc) (proc arg-vals)]
          [(FunV names body fun-env)
            ((compile body) (extend names arg-vals fun-env))]
          [else (error 'call ; this is *not* a compilation error
                        "function call with a non-function: ~s"
                        fval)]))]
      [(If cond-expr then-expr else-expr)
      (compile* (if (cases (compile* cond-expr)
                      [(RktV v) v] ; Racket value => use as boolean
                      [else #t])  ; other values are always true
                  then-expr
                  else-expr))])))

(: run : String -> Any)
;; evaluate a TOY program contained in a string
(define (run str)
  (let* ([compiled (compile (parse str))]
        [result  (compiled global-environment)])
    (cases result
      [(RktV v) v]
      [else (error 'run "evaluation returned a bad value: ~s"
                  result)])))

Not much changed, still. We curried the eval function and renamed it to compile. But when we actually call compile almost nothing happens — all it does is create a Racket closure which will do the rest of the work. (And this closure closes over the given expression.)

Running this “compiled” code is going to be very much like the previous usage of eval, except a little slower, because now every recursive call involves calling compile to generate a closure, which is then immediately used — so we just added some allocations at the recursive call points! (Actually, the extra cost is minimal because the Racket compiler will optimize away such immediate closure applications.)

Another way to see how this is not really a compiler yet is to consider when compile gets called. A proper compiler is something that does all of its work before running the code, which means that once it spits out the compiled code it shouldn’t be used again (except for compiling other code, of course). Our current code is not really a compiler since it breaks this feature. (For example, if GCC behaved this way, then it would “compile” files by producing code that invokes GCC to compile the next step, which, when run, invokes GCC again, etc.)

However, the conceptual change is substantial — we now have a function that does its work in two stages — the first part gets an expression and can do some compile-time work, and the second part does the run-time work, and includes anything inside the (lambda (env) …). The thing is that so far, the code does nothing at the compilation stage (remember: only creates a closure). But because we have two stages, we can now shift work from the second stage (the run-time) to the first (the compile-time).

For example, consider the following simple example:

#lang pl

(: foo : Number Number -> Number)
(define (foo x y)
  (* x y))

(: bar : Number -> Number)
(define (bar c)
  (: loop : Number Number -> Number)
  (define (loop n acc)
    (if (< 0 n)
        (loop (- n 1) (+ (foo c n) acc))
        acc))
  (loop 40000000 0))

(time (bar 0))

We can do the same thing here — separate foo it into two stages using currying, and modify bar appropriately:

#lang pl

(: foo : Number -> Number -> Number)
(define (foo x)
  (lambda (y)
    (* x y)))

(: bar : Number -> Number)
(define (bar c)
  (: loop : Number Number -> Number)
  (define (loop n acc)
    (if (< 0 n)
        (loop (- n 1) (+ ((foo c) n) acc))
        acc))
  (loop 40000000 0))

(time (bar 0))

Now instead of a simple multiplication, lets expand it a little, for example, do a case split on common cases where x is 0, 1, or 2:

(: foo : Number -> Number -> Number)
(define (foo x)
  (lambda (y)
    (cond [(= x 0) 0]
          [(= x 1) y]
          [(= x 2) (+ y y)] ; assume that this is faster
          [else (* x y)])))

This is not much faster, since Racket already optimizes multiplication in a similar way.

Now comes the real magic: deciding what branch of the cond to take depends only on x, so we can push the lambda inside:

(: foo : Number -> Number -> Number)
(define (foo x)
  (cond [(= x 0) (lambda (y) 0)]
        [(= x 1) (lambda (y) y)]
        [(= x 2) (lambda (y) (+ y y))]
        [else (lambda (y) (* x y))]))

We just made an improvement — the comparisons for the common cases are now done as soon as (foo x) is called, they’re not delayed to when the resulting function is used. Now go back to the way this is used in bar and make it call foo once for the given c:

#lang pl

(: foo : Number -> Number -> Number)
(define (foo x)
  (cond [(= x 0) (lambda (y) 0)]
        [(= x 1) (lambda (y) y)]
        [(= x 2) (lambda (y) (+ y y))]
        [else (lambda (y) (* x y))]))

(: bar : Number -> Number)
(define (bar c)
  (define foo-c (foo c))
  (: loop : Number Number -> Number)
  (define (loop n acc)
    (if (< 0 n)
        (loop (- n 1) (+ (foo-c n) acc))
        acc))
  (loop 40000000 0))

(time (bar 0))

Now foo-c is generated once, and if c happens to be one of the three common cases (as in the last expression), we can avoid doing any multiplication. (And if we hit the default case, then we’re doing the same thing we did before.)

[However, the result runs a little slower! The reason is that dealing with functions can have a higher cost when the compiler cannot “simplify closures away” — and this is what happens in the last version. The additional overhead is much higher than the multiplication we save (the Racket compiler inlines multiplications, so their cost is close to just executing a single machine-code instruction).]

Here is another useful example that demonstrates this:

(define (foo list)
  (map (lambda (n) (if ...something... E1 E2))
      list))

-->

(define (foo list)
  (map (if ...something...
        (lambda (n) E1)
        (lambda (n) E2))
      list))

(Question: when can you do that?)

This is not unique to Racket, it can happen in any language. Racket (or any language with first class function values) only makes it easy to create a local function that is specialized for the flag.


Getting our thing closer to a compiler is done in a similar way — we push the (lambda (env) ...) inside the various cases. (Note that compile* depends on the env argument, so it also needs to move inside — this is done for all cases that use it, and will eventually go away.) We actually need to use (lambda ([env : ENV]) ...) though, to avoid upsetting the type checker:

(: compile : TOY -> ENV -> VAL)
;; compiles TOY expressions to Racket functions.
(define (compile expr)
  (cases expr
    [(Num n)  (lambda ([env : ENV]) (RktV n))]
    [(Id name) (lambda ([env : ENV]) (lookup name env))]
    [(Bind names exprs bound-body)
    (lambda ([env : ENV])
      (: compile* : TOY -> VAL)
      (define (compile* expr) ((compile expr) env))
      ((compile bound-body)
        (extend names (map compile* exprs) env)))]
    [(Fun names bound-body)
    (lambda ([env : ENV]) (FunV names bound-body env))]
    [(Call fun-expr arg-exprs)
    (lambda ([env : ENV])
      (: compile* : TOY -> VAL)
      (define (compile* expr) ((compile expr) env))
      (let ([fval (compile* fun-expr)]
            [arg-vals (map compile* arg-exprs)])
        (cases fval
          [(PrimV proc) (proc arg-vals)]
          [(FunV names body fun-env)
            ((compile body) (extend names arg-vals fun-env))]
          [else (error 'call ; this is *not* a compilation error
                        "function call with a non-function: ~s"
                        fval)])))]
    [(If cond-expr then-expr else-expr)
    (lambda ([env : ENV])
      (: compile* : TOY -> VAL)
      (define (compile* expr) ((compile expr) env))
      (compile* (if (cases (compile* cond-expr)
                      [(RktV v) v] ; Racket value => use as boolean
                      [else #t])  ; other values are always true
                  then-expr
                  else-expr)))]))

and with this we shifted a bit of actual work to compile time — the code that checks what structure we have, and extracts its different slots. But this is still not good enough — it’s only the first top-level cases that is moved to compile-time — recursive calls to compile are still there in the resulting closures. This can be seen by the fact that we have those calls to compile in the Racket closures that are the results of our compiler, which, as discussed above, mean that it’s not an actual compiler yet.

For example, consider the Bind case:

[(Bind names exprs bound-body)
(lambda ([env : ENV])
  (: compile* : TOY -> VAL)
  (define (compile* expr) ((compile expr) env))
  ((compile bound-body)
    (extend names (map compile* exprs) env)))]

At compile-time we identify and deconstruct the Bind structure, then create a the runtime closure that will access these parts when the code runs. But this closure will itself call compile on bound-body and each of the expressions. Both of these calls can be done at compile time, since they only need the expressions — they don’t depend on the environment. Note that compile* turns to run here, since all it does is run a compiled expression on the current environment.

[(Bind names exprs bound-body)
(let ([compiled-body (compile bound-body)]
      [compiled-exprs (map compile exprs)])
  (lambda ([env : ENV])
    (: run : (ENV -> VAL) -> VAL)
    (define (run compiled-expr) (compiled-expr env))
    (compiled-body (extend names
                            (map run compiled-exprs)
                            env))))]

We can move it back up, out of the resulting functions, by making it a function that consumes an environment and returns a “caller” function:

(define (compile expr)
  ;; convenient helper
  (: caller : ENV -> (ENV -> VAL) -> VAL)
  (define (caller env)
    (lambda (compiled) (compiled env)))
  (cases expr
    ...
    [(Bind names exprs bound-body)
    (let ([compiled-body (compile bound-body)]
          [compiled-exprs (map compile exprs)])
      (lambda ([env : ENV])
        (compiled-body (extend names
                                (map (caller env) compiled-exprs)
                                env))))]
    ...))

Once this is done, we have a bunch of work that can happen at compile time: we pre-scan the main “bind spine” of the code.

We can deal in a similar way with other occurrences of compile calls in compiled code. The two branches that need to be fixed are:

  1. In the If branch, there is not much to do. After we make it pre-compile the cond-expr, we also need to make it pre-compile both the then-expr and the else-expr. This might seem like doing more work (since before changing it only one would get compiled), but since this is compile-time work, then it’s not as important. Also, if expressions are evaluated many times (being part of a loop, for example), so overall we still win.

  2. The Call branch is a little trickier: the problem here is that the expressions that are compiled are coming from the closure that is being applied. The solution for this is obvious: we need to change the closure type so that it closes over compiled expressions instead of over plain ones. This makes sense because closures are run-time values, so they need to close over the compiled expressions since this is what we use as “code” at run-time.

Again, the goal is to have no compile calls that happen at runtime: they should all happen before that. This would allow, for example, to obliterate the compiler once it has done its work, similar to how you don’t need GCC to run a C application. Yet another way to look at this is that we shouldn’t look at the AST at runtime — again, the analogy to GCC is that the AST is a data structure that the compiler uses, and it does not exist at runtime. Any runtime reference to the TOY AST is, therefore, as bad as any runtime reference to compile.

When we’re done with this process we’ll have something that is an actual compiler: translating TOY programs into Racket closures. To see how this is an actual compiler consider the fact that Racket uses a JIT to translate bytecode into machine code when it’s running functions. This means that the compiled version of our TOY programs are, in fact, translated all the way down to machine code.

Yet another way to see this is to change the compiler code so instead of producing a Racket closure it spits out the Racket code that makes up these closures when evaluated. For example, change

[(Bind names exprs bound-body)
(let ([compiled-body (compile bound-body)]
      [compiled-exprs (map compile exprs)])
  (lambda ([env : ENV])
    (compiled-body (extend ...))))]

into

[(Bind names exprs bound-body)
(let ([compiled-body (compile bound-body)]
      [compiled-exprs (map compile exprs)])
  (string-append
    "(lambda ([env : ENV]) ("
    compiled-body
    " (extend ...)))"))]

so we get a string that is a Racket program. But since we’re using a Lisp dialect, it’s generally better to use S-expressions instead:

[(Bind names exprs bound-body)
(let ([compiled-body (compile bound-body)]
      [compiled-exprs (map compile exprs)])
  `(lambda ([env : ENV])
      (,compiled-body (extend ...))))]

(Later in the course we’ll talk about these “`“s and “,“s. For now, it’s enough to know that “`” is kind of like a quote, and “,” is an unquote.)

Lazy Evaluation: Using a Lazy RacketTuesday, November 6th

PLAI §7 (done with Haskell)

For this part, we will use a new language, Lazy Racket.

#lang pl lazy

As the name suggests, this is a version of the normal (untyped) Racket language that is lazy.

First of all, let’s verify that this is indeed a lazy language:

> (define (foo x) 3)
> (foo (+ 1 "2"))
3

That went without a problem — the argument expression was indeed not evaluated. In this language, you can treat all expressions as future promises to evaluate. There are certain points where such promises are actually forced, all of these stem from some need to print a resulting value, in our case, it’s the REPL that prints such values:

> (+ 1 "2")
+: expects type <number> as 2nd argument,
given: "2"; other arguments were: 1

The expression by itself only generates a promise, but when we want to print it, this promise is forced to evaluate — this forces the addition, which forces its arguments (plain values rather than computation promises), and at this stage we get an error. (If we never want to see any results, then the language will never do anything at all.) So a promise is forced either when a value printout is needed, or if it is needed to recursively compute a value to print:

> (* 1 (+ 2 "3"))
+: expects type <number> as 2nd argument,
given: "3"; other arguments were: 2

Note that the error was raised by the internal expression: the outer expression uses *, and + requires actual values not promises.

Another example, which is now obvious, is that we can now define an if function:

> (define (my-if x y z) (if x y z))
> (my-if (< 1 2) 3 (+ 4 "5"))
3

Actually, in this language if, and, and or are all function values instead of special forms:

> (list if and or)
(#<procedure:if> #<procedure:and> #<procedure:or>)
> ((third (list if and or)) #t (+ 1 "two"))
#t

(By now, you should know that these have no value in Racket — using them like this in plain will lead to syntax errors.) There are some primitives that do not force their arguments. Constructors fall in this category, for example cons and list:

> (define (fib n) (if (<= n 1) n (+ (fib (- n 1)) (fib (- n 2)))))
> (define a (list (+ 1 2) (+ 3 "4") (fib 27) (* 5 6)))

Nothing — the definition simply worked, but that’s expected, since nothing is printed. If we try to inspect this value, we can get some of its parts, provided we do not force the bogus one:

> (first a)
3
> (fourth a)
30
> (third a)
196418
> (second a)
+: contract violation, expected: number?, given: "4" ...

The same holds for cons:

> (second (cons 1 (cons 2 (first null))))
2

Now if this is the case, then how about this:

> (define ones (cons 1 ones))

Everything is fine, as expected — but what is the value of ones now? Clearly, it is a list that has 1 as its first element:

> (first ones)
1

But what do we have in the tail of this list? We have ones which we already know is a list that has 1 in its first place — so following Racket’s usual rules, it means that the second element of ones is, again, 1. If we continue this, we can see that ones is, in fact, an infinite list of 1s:

> (second ones)
1
> (fifth ones)
1

In this sense, the way define behaves is that it defines a true equation: if ones is defined as (cons 1 ones), then the real value does satisfy

(equal? ones (cons 1 ones))

which means that the value is the fixpoint of the defined expression.

We can use append in a similar way:

> (define foo (append (list 1 2 3) foo))
> (fourth foo)
1

This looks like it has some common theme with the discussion of implementing recursive environments — it actually demonstrates that in this language, letrec can be used for simple values too. First of all, a side note — here an expression that indicated a bug in our substituting evaluator:

> (let ([x (list y)])
    (let ([y 1])
      x))
reference to undefined identifier: y

When our evaluator returned 1 for this, we noticed that this was a bug: it does not obey the lexical scoping rules. As seen above, Lazy Racket is correctly using lexical scope. Now we can go back to the use of letrec — what do we get by this definition:

> (define twos (let ([xs (cons 2 xs)]) xs))

we get an error about xs being undefined.

xs is unbound because of the usual scope that let uses. How can we make this work? — We simply use letrec:

> (define twos (letrec ([xs (cons 2 xs)]) xs))
> (first twos)
2

As expected, if we try to print an infinite list will cause an infinite loop, which DrRacket catches and prints in that weird way:

> twos
#0=(2 . #0#)

How would we inspect an infinite list? We write a function that returns part of it:

> (define (take n l)
    (if (or (<= n 0) (null? l))
      null
      (cons (first l) (take (sub1 n) (rest l)))))
> (take 10 twos)
(2 2 2 2 2 2 2 2 2 2)
> (define foo (append (list 1 2 3) foo))
> (take 10 foo)
(1 2 3 1 2 3 1 2 3 1)

Dealing with infinite lists can lead to lots of interesting things, for example:

> (define fibs (cons 1 (cons 1 (map + fibs (rest fibs)))))
> (take 10 fibs)
(1 1 2 3 5 8 13 21 34 55)

To see how it works, see what you know about fibs[n] which will be our notation for the nth element of fibs (starting from 1):

fibs[1] = 1  because of the first `cons'
fibs[2] = 1  because of the second `cons'

and for all n>2:

fibs[n] = (map + fibs (rest fibs))[n-2]
        = fibs[n-2] + (rest fibs)[n-2]
        = fibs[n-2] + fibs[n-2+1]
        = fibs[n-2] + fibs[n-1]

so it follows the exact definition of Fibonacci numbers.

Note that the list examples demonstrate that laziness applies to nested values (actually, nested computations) too: a value that is not needed is not computed, even if it is contained in a value that is needed. For example, in:

(define x (/ 1 0))
(if (list (+ 1 x)) 1 2)

the if needs to know only whether its first argument (note: it is an argument, since this if is a function) is #f or not. Once it is determined that it is a pair (a cons cell), there is no need to actually look at the values inside the pair, and therefore (+ 1 x) (and more specifically, x) is never evaluated and we see no error.

Lazy Evaluation: Some IssuesTuesday, November 6th

There are a few issues that we need to be aware of when we’re dealing with a lazy language. First of all, remember that our previous attempt at lazy evaluation has made

{with {x y}
  {with {y 1}
    x}}

evaluate to 1, which does not follow the rules of lexical scope. This is not a problem with lazy evaluation, but rather a problem with our naive implementation. We will shortly see a way to resolve this problem. In the meanwhile, remember that when we try the same in Lazy Racket we do get the expected error:

> (let ([x y])
    (let ([y 1])
      x))
reference to undefined identifier: y

A second issue is a subtle point that you might have noticed when we played with Lazy Racket: for some of the list values we have see a “.” printed. This is part of the usual way Racket displays an improper list — any list that does not terminate with a null value. For example, in plain Racket:

> (cons 1 2)
(1 . 2)
> (cons 1 (cons 2 (cons 3 4)))
(1 2 3 . 4)

In the dialect that we’re using in this course, this is not possible. The secret is that the cons that we use first checks that its second argument is a proper list, and it will raise an error if not. So how come Lazy Racket’s cons is not doing the same thing? The problem is that to know that something is a proper list, we will have to force it, which will make it not behave like a constructor.

As a side note, we can achieve some of this protection if we don’t insist on immediately checking the second argument completely, and instead we do the check when needed — lazily:

(define (safe-cons x l)
  (cons x (if (pair? l) l (error "poof"))))

Finally, there are two consequences of using a lazy language that make it more difficult to debug (or at lease take some time to get used to). First of all, control tends to flow in surprising ways. For example, enter the following into DrRacket, and run it in the normal language level for the course:

                (define (foo3 x)
                  (/ x "1"))
(define (foo2 x)
  (foo3 x))
                (define (foo1 x)
                  (list (foo2 x)))
(define (foo0 x)
  (first (foo1 x)))

        (+ 1 (foo0 3))

In the normal language level, we get an error, and red arrows that show us how where in the computation the error was raised. The arrows are all expected, except that foo2 is not in the path — why is that? Remember the discussion about tail-calls and how they are important in Racket since they are the only tool to generate loops? This is what we’re seeing here: foo2 calls foo3 in a tail position, so there is no need to keep the foo2 context anymore — it is simply replaced by foo3. (Incidentally, there is also no arrow that goes through foo1: Racket does some smart inlining, and it figures out that foo0+foo1 are simply returning the same value, so it skips foo1.)

Now switch to Lazy Racket and re-run — you’ll see no arrows at all. What’s the problem? The call of foo0 creates a promise that is forced in the top-level expression, that simply returns the first of the list that foo1 created — and all of that can be done without forcing the foo2 call. Going this way, the computation is finally running into an error after the calls to foo0, foo1, and foo2 are done — so we get the seemingly out-of-context error.

To follow what’s happening here, we need to follow how promise are forced: when we have code like

> (define (foo x) (/ x 0))
> (foo 9)

then the foo call is a strict point, since we need an actual value to display on the REPL. Since it’s in a strict position, we do the call, but when we’re in the function there is no need to compute the division result — so it is returned as a lazy promise value back to the toplevel. It is only then that we continue the process of getting an actual value, which leads to trying to compute the division and get the error.

Finally, there are also potential problems when you’re not careful about memory use. A common technique when using a lazy language is to generate an infinite list and pull out its Nth element. For example, to compute the Nth Fibonacci number, we’ve seen how we can do this:

(define fibs (cons 1 (cons 1 (map + fibs (rest fibs)))))
(define (fib n) (list-ref fibs n))

and we can also do this (reminder: letrec is the same as an internal definition):

(define (fib n)
  (letrec ([fibs (cons 1 (cons 1 (map + fibs (rest fibs))))])
    (list-ref fibs n))) ; tail-call => no need to keep `fibs`

but the problem here is that when list-ref is making its way down the list, it might still hold a reference to fibs, which means that as the list is forced, all intermediate values are held in memory. In the first of these two, this is guaranteed to happen since we have a binding that points at the head of the fibs list. With the second form things can be confusing: it might be that our language implementation is smart enough to see that fibs is not really needed anymore and release the offending reference. If it isn’t, then we’d have to do something like

(define (fib n)
  (list-ref
  (letrec ([fibs (cons 1 (cons 1 (map + fibs (rest fibs))))])
    fibs)
  n))

to eliminate it. But even if the implementation does know that there is no need for that reference, there are other tricky situations that are hard to avoid.

Side note: Racket didn’t use to do this optimization, but now it does, and the lazy language helped in clarifying more cases where references should be released. To check that, consider these two variants:

(define (fib1 n)
  (letrec ([fibs (cons 1 (cons 1 (map + fibs (rest fibs))))])
    (if (number? (list-ref fibs n))
        "a number"
        "not a number")))
(define (fib2 n)
  (letrec ([fibs (cons 1 (cons 1 (map + fibs (rest fibs))))])
    (if (number? (list-ref fibs n))
        "a number"
        (error 'fib "the list starting with ~s is broken"
              (first fibs)))))

If we try to use them with a big input:

(fib1 300000) ; or fib2

then fib1 would work file, whereas fib2 will likely run into DrRacket’s memory limit and the computation will be terminated. The problem is that fib2 uses the fibs2 value after the list-ref call, which will make a reference to the head of the list, preventing it to be garbage-collected while list-ref is cdr-ing down the list, making more links materialize.

Lazy Evaluation: Shell ExamplesTuesday, November 6th

There is a very simple and elegant principle in shell programming — we get a single data type, a character stream, and many small functions, each doing a single simple job. With these small building blocks, we can construct more sequences that achieve more complex tasks, for example — a sorted frequency table of lines in a file:

sort foo | uniq -c | sort -nr

This is very much like a programming language — we get small blocks, and build stuff out of them. Of course there are swiss army knives like awk that try to do a whole bunch of stuff, (the same attitude that brought Perl to the world…) and even these respect the “stream” data type. For example, a simple { print $1 } statement will work over all lines, one by one, making it a program over an infinite input stream, which is what happens in reality in something like:

cat /dev/console | awk ...

But there is something else in shell programming that makes so effective: it is implementing a sort of a lazy evaluation. For example, compare this:

cat foo | awk '{ print $1+$2; }' | uniq

to:

cat foo | awk '{ print $1+$2; }' | uniq | head -5

Each element in the pipe is doing its own small job, and it is always doing just enough to feed its output. Each basic block is designed to work even on infinite inputs! (Even sort works on unlimited inputs…) (Soon we will see a stronger connection with lazy evaluation.)

Side note: (Alan Perlis) “It is better to have 100 functions operate on one data structure than 10 functions on 10 data structures”… But the uniformity comes at a price: the biggest problem shells have is in their lack of a recursive structure, contaminating the world with way too many hacked up solutions. More than that, it is extremely inefficient and usually leads to data being re-parsed over and over and over — each small Unix command needs to always output stuff that is human readable, but the next command in the pipe will need to re-parse that, eg, rereading decimal numbers. If you look at pipelines as composing functions, then a pipe of numeric commands translates to something like:

itoa(baz(atoi(itoa(bar(atoi(itoa(foo(atoi(inp)))))))))

and it is impossible to get rid of the redundant atoi(itoa(...))s.

Lazy Evaluation: Programming ExamplesTuesday, November 13th

We already know that when we use lazy evaluation, we are guaranteed to have more robust programs. For example, a function like:

(define (my-if x y z)
  (if x y z))

is completely useless in Racket because all functions are eager, but in a lazy language, it would behave exactly like the real if. Note that we still need some primitive conditional, but this primitive can be a function (and it is, in Lazy Racket).

But we get more than that. If we have a lazy language, then computations are pushed around as if they were values (computations, because these are expressions that are yet to be evaluated). In fact, there is no distinction between computations and values, it just happens that some values contain “computational promises”, things that will do something in the future.

To see how this happens, we write a simple program to compute the (infinite) list of prime numbers using the sieve of Eratosthenes. To do this, we begin by defining the list of all natural numbers:

(define nats (cons 1 (map add1 nats)))

And now define a sift function: it receives an integer n and an infinite list of integers l, and returns a list without the numbers that can be divided by n. This is simple to write using filter:

(define (sift n l)
  (filter (lambda (x) (not (divides? n x))) l))

and it requires a definition for divides? — we use Racket’s modulo for this:

(define (divides? n m)
  (zero? (modulo m n)))

Now, a sieve is a function that consumes a list that begins with a prime number, and returns the prime numbers from this list. To do this, it returns a list that has the same first number, and for its tail it sifts out numbers that are divisible by the first from the original list’s tail, and calls itself recursively on the result:

(define (sieve l)
  (cons (first l) (sieve (sift (first l) (rest l)))))

Finally, the list of prime numbers is the result of applying sieve on the list of numbers from 2. The whole program is now:

#lang pl lazy

(define nats (cons 1 (map add1 nats)))

(define (divides? n m)
  (zero? (modulo m n)))

(define (sift n l)
  (filter (lambda (x) (not (divides? n x))) l))

(define (sieve l)
  (cons (first l) (sieve (sift (first l) (rest l)))))

(define primes (sieve (rest nats)))

To see how this runs, we trace modulo to see which tests are being used. The effect of this is that each time divides? is actually required to return a value, we will see a line with its inputs, and its output. This output looks quite tricky — things are computed only on a “need to know” basis, meaning that debugging lazy programs can be difficult, since things happen when they are needed which takes time to get used to. However, note that the program actually performs the same tests that you’d do using any eager-language implementation of the sieve of Eratosthenes, and the advantage is that we don’t need to decide in advance how many values we want to compute — all values will be computed when you want to see the corresponding result. Implementing this behavior in an eager language is more difficult than a simple program, yet we don’t need such complex code when we use lazy evaluation.

Note that if we trace divides? we see results that are some promise struct — these are unevaluated expressions, and they point at the fact that when divides? is used, it doesn’t really force its arguments — this happens later when these results are forced.

The analogy with shell programming using pipes should be clear now — for example, we have seen this:

cat foo | awk '{ print $1+$2; }' | uniq | head -5

The last head -5 means that no computation is done on parts of the original file that are not needed. It is similar to a (take 5 l) expression in Lazy Racket.

Side Note: Similarity to Generators and ChannelsTuesday, November 13th

Using infinite lists is similar to using channels — a tool for synchronizing threads and (see a Rob Pike’s talk), and generators (as they exist in Python). Here are examples of both, note how similar they both are, and how similar they are to the above definition of primes. (But note that there is an important difference, can you see it? It has to be with whether a stream is reusable or not.)

First, the threads & channels version:

#lang racket

(define-syntax-rule (bg expr ...) (thread (lambda () expr ...)))

(define nats
  (let ([out (make-channel)])
    (define (loop i) (channel-put out i) (loop (add1 i)))
    (bg (loop 1))
    out))

(define (divides? n m)
  (zero? (modulo m n)))

(define (filter pred c)
  (define out (make-channel))
  (define (loop)
    (let ([x (channel-get c)])
      (when (pred x) (channel-put out x))
      (loop)))
  (bg (loop))
  out)

(define (sift n c)
  (filter (lambda (x) (not (divides? n x))) c))

(define (sieve c)
  (define out (make-channel))
  (define (loop c)
    (define first (channel-get c))
    (channel-put out first)
    (loop (sift first c)))
  (bg (loop c))
  out)

(define primes
  (begin (channel-get nats) (sieve nats)))

(define (take n c)
  (if (zero? n) null (cons (channel-get c) (take (sub1 n) c))))

(take 10 primes)

And here is the generator version:

#lang racket

(require racket/generator)

(define nats
  (generator ()
    (define (loop i)
      (yield i)
      (loop (add1 i)))
    (loop 1)))

(define (divides? n m)
  (zero? (modulo m n)))

(define (filter pred g)
  (generator ()
    (define (loop)
      (let ([x (g)])
        (when (pred x) (yield x))
        (loop)))
    (loop)))

(define (sift n g)
  (filter (lambda (x) (not (divides? n x))) g))

(define (sieve g)
  (define (loop g)
    (define first (g))
    (yield first)
    (loop (sift first g)))
  (generator () (loop g)))

(define primes
  (begin (nats) (sieve nats)))

(define (take n g)
  (if (zero? n) null (cons (g) (take (sub1 n) g))))

(take 10 primes)

Call by Need vs Call by NameTuesday, November 13th

Finally, note that on requiring different parts of the primes, the same calls are not repeated. This indicates that our language implements “call by need” rather than “call by name”: once an expression is forced, its value is remembered, so subsequent usages of this value do not require further computations.

Using “call by name” means that we actually use expressions which can lead to confusing code. An old programming language that used this is Algol. A confusing example that demonstrates this evaluation strategy is:

#lang algol60
begin
  integer procedure SIGMA(x, i, n);
    value n;
    integer x, i, n;
  begin
    integer sum;
    sum := 0;
    for i := 1 step 1 until n do
      sum := sum + x;
    SIGMA := sum;
  end;
  integer q;
  printnln(SIGMA(q*2-1, q, 7));
end

x and i are arguments that are passed by name, which means that they can use the same memory location. This is called aliasing, a problem that happens when pointers are involved (eg, pointers in C and reference arguments in C++).

Example of Feature EmbeddingTuesday, November 13th

Another interesting behavior that we can now observe, is that the TOY evaluation rule for with:

eval({with {x E1} E2}) = eval(E2[eval(E1)/x])

is specifying an eager evaluator only if the language that this rule is written in is itself eager. Indeed, if we run the TOY interpreter in Lazy Racket (or other interpreters we have implemented), we can verify that running:

(run "{bind {{x {/ 1 0}}} 1}")

is perfectly fine — the call to Racket’s division is done in the evaluation of the TOY division expression, but since Lazy Racket is lazy, then if this value is never used then we never get to do this division! On the other hand, if we evaluate

(run "{bind {{x {/ 1 0}}} {+ x 1}}")

we do get an error when DrRacket tries to display the result, which forces strictness. Note how the arrows in DrRacket that show where the computation is are quite confusing: the computation seem to go directly to the point of the arithmetic operations (arith-op) since the rest of the evaluation that the evaluator performed was already done, and succeeded. The actual failure happens when we try to force the resulting promise which contains only the strict points in our code.

Implementing Laziness (in plain Racket)Tuesday, November 13th

PLAI §8

Generally, we know how lazy evaluation works when we use the substitution model. We even know that if we have:

{bind {{x y}}
  {bind {{y 2}}
    {+ x y}}}

then the result should be an error because we cannot substitute the y expression in because it will capture the y — changing the binding structure. As an indication, the original expression contains a free reference to y, which is exactly why we shouldn’t substitute it. But what about:

{bind {{x {+ 4 5}}}
  {bind {{y {+ x x}}}
    {bind {{z y}}
      {bind {{x 4}}
        z}}}}

Evaluating this eagerly returns 18, we therefore expect any other evaluation (eager or lazy, using substitutions or environments) to return 18 too, because any of these options should not change the meaning of numbers, of addition, or of the scoping rules. (And we know that no matter what evaluation strategy we choose, if we get to a value (no infinite loop or exception) then it’ll always be the same value.) For example, try using lazy evaluation with substitutions:

{bind {{x {+ 4 5}}}
  {bind {{y {+ x x}}}
    {bind {{z y}}
      {bind {{x 4}}
        z}}}}
-->
{bind {{y {+ {+ 4 5} {+ 4 5}}}}
  {bind {{z y}}
    {bind {{x 4}}
      z}}}
-->
{bind {{z {+ {+ 4 5} {+ 4 5}}}}
  {bind {{x 4}}
    z}}
-->
{bind {{x 4}}
  {+ {+ 4 5} {+ 4 5}}}
-->
{+ {+ 4 5} {+ 4 5}}
-->
{+ 9 9}
-->
18

And what about lazy evaluation using environments:

{bind {{x {+ 4 5}}}
  {bind {{y {+ x x}}}
    {bind {{z y}}
      {bind {{x 4}}
        z}}}}        []
-->
{bind {{y {+ x x}}}
  {bind {{z y}}
    {bind {{x 4}}
      z}}}            [x:={+ 4 5}]
-->
{bind {{z y}}
  {bind {{x 4}}
    z}}              [x:={+ 4 5}, y:={+ x x}]
-->
{bind {{x 4}}
  z}                  [x:={+ 4 5}, y:={+ x x}, z:=y]
-->
z                    [x:=4, y:={+ x x}, z:=y]
-->
y                    [x:=4, y:={+ x x}, z:=y]
-->
{+ x x}              [x:=4, y:={+ x x}, z:=y]
-->
{+ 4 4}              [x:=4, y:={+ x x}, z:=y]
-->
8                    [x:=4, y:={+ x x}, z:=y]

We have a problem! This problem should be familiar now, it is very similar to the problem that led us down the mistaken path of dynamic scoping when we tried to have first-class functions. In both cases, substitution always worked, and it looks like in both cases the problem is that we don’t remember the environment of an expression: in the case of functions, it is the environment at the time of creating the closure that we want to capture and use when we go back later to evaluate the body of the function. Here we have a similar situation, except that we don’t need a function to defer computation: most expressions get evaluated at some time in the future, so every time we defer such a computation we need to remember the lexical environment of the expression.

This is the major point that will make things work again: every expression creates something like a closure — an object that closes over an expression and an environment at the (lexical) place where that expression was used, and when we actually want to evaluate it later, we need to do it in the right lexical context. So it is like a closure except it doesn’t need to be applied, and there are no arguments. In fact it is also a form of a closure — instead of closing over a function body and an environment, it closes over any expression and an environment. (As we shall see, lazy evaluation is tightly related to using nullary functions: thunks.)

Sloth: A Lazy EvaluatorTuesday, November 13th

So we implement this by creating such closure values for all expressions that are not evaluated right now. We begin with the Toy language, and rename it to “Sloth”. We then add one more case to the data type of values which implements the new kind of expression closures, which contains the expression and its environment:

(define-type VAL
  [RktV  Any]
  [FunV  (Listof Symbol) SLOTH ENV]
  [ExprV                SLOTH ENV] ;*** new: expression and scope
  [PrimV ((Listof VAL) -> VAL)])

(Intuition#1: ExprV is a delayed evaluation and therefore it has the two values that are ultimately passed to eval. Intuition#2: laziness can be implemented with thunks, so we hold the same information as a FunV does, only there’s no need for the argument names.)

Where should we use the new ExprV? — At any place where we want to be lazy and defer evaluating an expression for later. The two places in the interpreter where we want to delay evaluation are the named expressions in a bind form and the argument expressions in a function application. Both of these cases use the helper eval* function to do their evaluations, for example:

[(Bind names exprs bound-body)
(eval bound-body (extend names (map eval* exprs) env))]

To delay these evaluations, we need to change eval* so it returns an expression closure instead of actually doing the evaluation — change:

(: eval* : SLOTH -> VAL)
(define (eval* expr) (eval expr env))

to:

(: eval* : SLOTH -> VAL)
(define (eval* expr) (ExprV expr env))

Note how simple this change is — instead of an eval function call, we create a value that contains the parts that would have been used in the eval function call. This value serves as a promise to do this evaluation (the eval call) later, if needed. (This is exactly why a Lazy Racket would make this a lazy evaluator: in it, all function calls are promises.)


Side note: this can be used in any case when you’re using an eager language, and you want to delay some function call — all you need to do is replace (using a C-ish syntax)

int foo(int x, str y) {
  ...do some work...
}

with

// rename `foo':
int real_foo(int x, str y) {
  ...same work...
}

// `foo' is a delayed constructor, instead of a plain function
struct delayed_foo {
  int x;
  str y;
}
delayed_foo foo(int x, str y) {
  return new delayed_foo(x, y);
}

now all calls to foo return a delayed_foo instance instead of an integer. Whenever we want to force the delayed promise, we can use this function:

int force_foo(delayed_foo promise) {
  return real_foo(promise.x, promise.y);
}

You might even want to make sure that each such promise is evaluated exactly once — this is simple to achieve by adding a cache field to the struct:

int real_foo(int x, str y) {
  ...same work...
}

struct delayed_foo {
  int  x;
  str  y;
  bool is_computed;
  int  result;
}
delayed_foo foo(int x, str y) {
  return new delayed_foo(x, y, false, 0);
}

int force_foo(delayed_foo promise) {
  if (!promise.is_computed) {
    promise.result = real_foo(promise.x, promise.y);
    promise.is_computed = true;
  }
  return promise.result;
}

As we will see shortly, this corresponds to switching from a call-by-name lazy language to a call-by-need one.


Back to our Sloth interpreter — given the eval* change, we expect that eval-uating:

{bind {{x 1}} x}

will return:

(ExprV (Num 1) ...the-global-environment...)

and the same goes for eval-uating

{{fun {x} x} 1}

Similarly, evaluating

{bind {{x {+ 1 2}}} x}

should return

(ExprV (Call (Id +) (Num 1) (Num 2)) ...the-global-environment...)

But what about evaluating an expression like this one:

{bind {{x 2}}
  {+ x x}}

?

Using what we have so far, we will get to evaluate the body, which is a (Call …) expression, but when we evaluate the arguments for this function call, we will get ExprV values — so we will not be able to perform the addition. Instead, we will get an error from the function that racket-func->prim-val creates, due to the value being an ExprV instead of a RktV.

What we really want is to actually add two values, not promises. So maybe distinguish the two applications — treat PrimV differently from FunV closures?

(: eval* : SLOTH -> VAL)
(define (eval* expr) (ExprV expr env))
(: real-eval* : SLOTH -> VAL)
(define (real-eval* expr) (eval expr env))
(cases expr
  ...
  [(Call fun-expr arg-exprs)
  (let ([fval (eval fun-expr env)]
        ;; move: [arg-vals (map eval* arg-exprs)]
        )
    (cases fval
      [(PrimV proc) (proc (map real-eval* arg-exprs))] ; change
      [(FunV names body fun-env)
        (eval body (extend names (map eval* arg-exprs) fun-env))]
      ...))]
  ...)

This still doesn’t work — the problem is that the function now gets a bunch of values, where some of these can still be ExprVs because the evaluation itself can return such values… Another way to see this problem is to consider the code for evaluating an If conditional expression:

[(If cond-expr then-expr else-expr)
(eval* (if (cases (real-eval* cond-expr)
              [(RktV v) v] ; Racket value => use as boolean
              [else #t])  ; other values are always true
          then-expr
          else-expr))]

…we need to take care of a possible ExprV here. What should we do? The obvious solution is to use eval if we get an ExprV value:

[(If cond-expr then-expr else-expr)
(eval* (if (cases (real-eval* cond-expr)
              [(RktV v) v] ; Racket value => use as boolean
              [(ExprV expr env) (eval expr env)] ; force a promise
              [else #t])  ; other values are always true
          then-expr
          else-expr))]

Note how this translates back the data structure that represents a delayed eval promise back into a real eval call…

Going back to our code for Call, there is a problem with it — the

(define (real-eval* expr) (eval expr env))

will indeed evaluate the expression instead of lazily deferring this to the future, but this evaluation might itself return such lazy values. So we need to inspect the resulting value again, forcing the promise if needed:

(define (real-eval* expr)
  (let ([val (eval expr env)])
    (cases val
      [(ExprV expr env) (eval expr env)]
      [else val])))

But we still have a problem — programs can get an arbitrarily long nested chains of ExprVs that get forced to other ExprVs.

{bind {{x true}}
  {bind {{y x}}
    {bind {{z y}}
      {if z
        {foo}
        {bar}}}}}

What we really need is to write a loop that keeps forcing promises over and over until it gets a proper non-ExprV value.

(: strict : VAL -> VAL)
;; forces a (possibly nested) ExprV promise,
;; returns a VAL that is not an ExprV
(define (strict val)
  (cases val
    [(ExprV expr env) (strict (eval expr env))] ; loop back
    [else val]))

Note that it’s close to real-eval*, but there’s no need to mix it with eval. The recursive call is important: we can never be sure that eval didn’t return an ExprV promise, so we have to keep looping until we get a “real” value.

Now we can change the evaluation of function calls to something more manageable:

[(Call fun-expr arg-exprs)
(let ([fval (strict (eval* fun-expr))]          ;*** strict!
      [arg-vals (map eval* arg-exprs)])
  (cases fval
    [(PrimV proc) (proc (map strict arg-vals))] ;*** strict!
    [(FunV names body fun-env)
      (eval body (extend names arg-vals fun-env))]
    [else (error 'eval "function call with a non-function: ~s"
                  fval)]))]

The code is fairly similar to what we had previously — the only difference is that we wrap a strict call where a proper value is needed — the function value itself, and arguments to primitive functions.

The If case is similar (note that it doesn’t matter if strict is used with the result of eval or eval* (which returns an ExprV)):

[(If cond-expr then-expr else-expr)
(eval* (if (cases (strict (eval* cond-expr))
              [(RktV v) v] ; Racket value => use as boolean
              [else #t])  ; other values are always true
          then-expr
          else-expr))]

Note that, like before, we always return #t for non-RktV values — this is because we know that the value there is never an ExprV. All we need now to get a working evaluator, is one more strictness point: the outermost point that starts our evaluation — run — needs to use strict to get a proper result value.

(: run : String -> Any)
;; evaluate a SLOTH program contained in a string
(define (run str)
  (let ([result (strict (eval (parse str) global-environment))])
    (cases result
      [(RktV v) v]
      [else (error 'run "evaluation returned a bad value: ~s"
                  result)])))

With this, all of the tests that we took from the Toy evaluator run successfully. To make sure that the interpreter is lazy, we can add a test that will fail if the language is strict:

;; Test laziness
(test (run "{{fun {x} 1} {/ 9 0}}") => 1)
(test (run "{{fun {x} 1} {{fun {x} {x x}} {fun {x} {x x}}}}") => 1)
(test (run "{bind {{x {{fun {x} {x x}} {fun {x} {x x}}}}} 1}") => 1)

[In fact, we can continue and replace all eval calls with ExprV, leaving only the one call in strict. This doesn’t make any difference, because the resulting promises will eventually be forced by strict anyway.]

Getting more from SlothTuesday, November 13th

As we’ve seen, using strict in places where we need an actual value rather than a delayed promise is enough to get a working lazy evaluator. Our current implementation assumes that all primitive functions need strict values, therefore the argument values are all passed through the strict function — but this is not always the case. Specifically, if we have constructor functions, then we don’t need (and usually don’t want) to force the promises. This is basically what allows us to use infinite lists in Lazy Racket: the fact that list and cons do not require forcing their arguments.

To allow some primitive functions to consume strict values and some to leave them as is, we’re going to change racket-func->prim-val and add a flag that indicates whether the primitive function is strict or not. Obviously, we also need to move the strict call around arguments to a primitive function application into the racket-func->prim-val generated function — which simplifies the Call case in eval (we go from (proc (map strict arg-vals)) back to (proc arg-vals)). The new code for racket-func->prim-val and its helper is:

(: unwrap-rktv : VAL -> Any)
;; helper for `racket-func->prim-val': strict and unwrap a RktV
;; wrapper in preparation to be sent to the primitive function
(define (unwrap-rktv x)
  (let ([s (strict x)])
    (cases s
      [(RktV v) v]
      [else (error 'racket-func "bad input: ~s" s)])))

(: racket-func->prim-val : Function Boolean -> VAL)
;; converts a racket function to a primitive evaluator function ...
(define (racket-func->prim-val racket-func strict?)
  (define list-func (make-untyped-list-function racket-func))
  (PrimV (lambda (args)
          (let ([args (if strict?
                        (map unwrap-rktv args)
                        args)])  ;*** use values as is!
            (RktV (list-func args))))))

We now need to annotate the primitives in the global environment, as well as add a few constructors:

;; The global environment has a few primitives:
(: global-environment : ENV)
(define global-environment
  (FrameEnv (list (list '+ (racket-func->prim-val + #t))
                  (list '- (racket-func->prim-val - #t))
                  (list '* (racket-func->prim-val * #t))
                  (list '/ (racket-func->prim-val / #t))
                  (list '< (racket-func->prim-val < #t))
                  (list '> (racket-func->prim-val > #t))
                  (list '= (racket-func->prim-val = #t))
                  ;; note flags:
                  (list 'cons  (racket-func->prim-val cons  #f))
                  (list 'list  (racket-func->prim-val list  #f))
                  (list 'first (racket-func->prim-val first #t))
                  (list 'rest  (racket-func->prim-val rest  #t))
                  (list 'null? (racket-func->prim-val null? #t))
                  ;; values
                  (list 'true  (RktV #t))
                  (list 'false (RktV #f))
                  (list 'null  (RktV null)))
            (EmptyEnv)))

Note that this last change raises a subtle type issue: we’re actually abusing the Racket list and cons constructors to hold Sloth values. One way in which this becomes a problem is the current assumption that a primitive function always returns a Racket value (it is always wrapped in a RktV) — but this is no longer the case for first and rest: when we use

{cons 1 null}

in Sloth, the resulting value will be

(RktV (cons (ExprV (Num 1) ...) (ExprV (Id null) ...)))

so if we try and grab the first value of this

{first {cons 1 null}}

we will eventually get back the ExprV and wrap it in a RktV:

(RktV (ExprV (Num 1) ...))

and finally run will strip off the RktV and return the ExprV. A solution to this is to make our first and rest functions return a value without wrapping it in a RktV — we can identify this situation by the fact that the returned value is already a VAL instead of some other Racket value. We can identify such values with the VAL? predicate that gets defined by our define-type, implemented by a new wrap-in-val helper:

(: unwrap-rktv : VAL -> Any)
;; helper for `racket-func->prim-val': strict and unwrap a RktV
;; wrapper in preparation to be sent to the primitive function
(define (unwrap-rktv x)
  (let ([s (strict x)])
    (cases s
      [(RktV v) v]
      [else (error 'racket-func "bad input: ~s" s)])))

(: wrap-in-val : Any -> VAL)
;; helper that ensures a VAL output using RktV wrapper when needed,
;; but leaving as is otherwise
(define (wrap-in-val x)
  (if (VAL? x) x (RktV x)))

(: racket-func->prim-val : Function Boolean -> VAL)
;; converts a racket function to a primitive evaluator function ...
(define (racket-func->prim-val racket-func strict?)
  (define list-func (make-untyped-list-function racket-func))
  (PrimV (lambda (args)
          (let ([args (if strict? (map unwrap-rktv args) args)])
            (wrap-in-val (list-func args))))))

Note that we don’t need to worry about the result being an ExprV — that will eventually be taken care of by strict.

The complete Sloth code follows. It can be used to do the same fun things we did with Lazy Racket.

#lang pl

;;; ----------------------------------------------------------------
;;; Syntax

#| The BNF:
  <SLOTH> ::= <num>
            | <id>
            | { bind {{ <id> <SLOTH> } ... } <SLOTH> }
            | { fun { <id> ... } <SLOTH> }
            | { if <SLOTH> <SLOTH> <SLOTH> }
            | { <SLOTH> <SLOTH> ... }
|#

;; A matching abstract syntax tree datatype:
(define-type SLOTH
  [Num  Number]
  [Id  Symbol]
  [Bind (Listof Symbol) (Listof SLOTH) SLOTH]
  [Fun  (Listof Symbol) SLOTH]
  [Call SLOTH (Listof SLOTH)]
  [If  SLOTH SLOTH SLOTH])

(: unique-list? : (Listof Any) -> Boolean)
;; Tests whether a list is unique, guards Bind and Fun values.
(define (unique-list? xs)
  (or (null? xs)
      (and (not (member (first xs) (rest xs)))
          (unique-list? (rest xs)))))

(: parse-sexpr : Sexpr -> SLOTH)
;; parses s-expressions into SLOTHs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(cons 'bind more)
    (match sexpr
      [(list 'bind (list (list (symbol: names) (sexpr: nameds))
                          ...)
          body)
        (if (unique-list? names)
          (Bind names (map parse-sexpr nameds) (parse-sexpr body))
          (error 'parse-sexpr "duplicate `bind' names: ~s" names))]
      [else (error 'parse-sexpr "bad `bind' syntax in ~s" sexpr)])]
    [(cons 'fun more)
    (match sexpr
      [(list 'fun (list (symbol: names) ...) body)
        (if (unique-list? names)
          (Fun names (parse-sexpr body))
          (error 'parse-sexpr "duplicate `fun' names: ~s" names))]
      [else (error 'parse-sexpr "bad `fun' syntax in ~s" sexpr)])]
    [(cons 'if more)
    (match sexpr
      [(list 'if cond then else)
        (If (parse-sexpr cond)
            (parse-sexpr then)
            (parse-sexpr else))]
      [else (error 'parse-sexpr "bad `if' syntax in ~s" sexpr)])]
    [(list fun args ...) ; other lists are applications
    (Call (parse-sexpr fun)
          (map parse-sexpr args))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

(: parse : String -> SLOTH)
;; Parses a string containing an SLOTH expression to a SLOTH AST.
(define (parse str)
  (parse-sexpr (string->sexpr str)))

;;; ----------------------------------------------------------------
;;; Values and environments

(define-type ENV
  [EmptyEnv]
  [FrameEnv FRAME ENV])

;; a frame is an association list of names and values.
(define-type FRAME = (Listof (List Symbol VAL)))

(define-type VAL
  [RktV  Any]
  [FunV  (Listof Symbol) SLOTH ENV]
  [ExprV SLOTH ENV]
  [PrimV ((Listof VAL) -> VAL)])

(: extend : (Listof Symbol) (Listof VAL) ENV -> ENV)
;; extends an environment with a new frame.
(define (extend names values env)
  (if (= (length names) (length values))
    (FrameEnv (map (lambda ([name : Symbol] [val : VAL])
                    (list name val))
                  names values)
              env)
    (error 'extend "arity mismatch for names: ~s" names)))

(: lookup : Symbol ENV -> VAL)
;; lookup a symbol in an environment, frame by frame,
;; return its value or throw an error if it isn't bound
(define (lookup name env)
  (cases env
    [(EmptyEnv) (error 'lookup "no binding for ~s" name)]
    [(FrameEnv frame rest)
    (let ([cell (assq name frame)])
      (if cell
        (second cell)
        (lookup name rest)))]))

(: unwrap-rktv : VAL -> Any)
;; helper for `racket-func->prim-val': strict and unwrap a RktV
;; wrapper in preparation to be sent to the primitive function
(define (unwrap-rktv x)
  (let ([s (strict x)])
    (cases s
      [(RktV v) v]
      [else (error 'racket-func "bad input: ~s" s)])))

(: wrap-in-val : Any -> VAL)
;; helper that ensures a VAL output using RktV wrapper when needed,
;; but leaving as is otherwise
(define (wrap-in-val x)
  (if (VAL? x) x (RktV x)))

(: racket-func->prim-val : Function Boolean -> VAL)
;; converts a racket function to a primitive evaluator function
;; which is a PrimV holding a ((Listof VAL) -> VAL) function.
;; (the resulting function will use the list function as is,
;; and it is the list function's responsibility to throw an error
;; if it's given a bad number of arguments or bad input types.)
(define (racket-func->prim-val racket-func strict?)
  (define list-func (make-untyped-list-function racket-func))
  (PrimV (lambda (args)
          (let ([args (if strict? (map unwrap-rktv args) args)])
            (wrap-in-val (list-func args))))))

;; The global environment has a few primitives:
(: global-environment : ENV)
(define global-environment
  (FrameEnv (list (list '+ (racket-func->prim-val + #t))
                  (list '- (racket-func->prim-val - #t))
                  (list '* (racket-func->prim-val * #t))
                  (list '/ (racket-func->prim-val / #t))
                  (list '< (racket-func->prim-val < #t))
                  (list '> (racket-func->prim-val > #t))
                  (list '= (racket-func->prim-val = #t))
                  ;; note flags:
                  (list 'cons  (racket-func->prim-val cons  #f))
                  (list 'list  (racket-func->prim-val list  #f))
                  (list 'first (racket-func->prim-val first #t))
                  (list 'rest  (racket-func->prim-val rest  #t))
                  (list 'null? (racket-func->prim-val null? #t))
                  ;; values
                  (list 'true  (RktV #t))
                  (list 'false (RktV #f))
                  (list 'null  (RktV null)))
            (EmptyEnv)))

;;; ----------------------------------------------------------------
;;; Evaluation

(: strict : VAL -> VAL)
;; forces a (possibly nested) ExprV promise, returns a VAL that is
;; not an ExprV
(define (strict val)
  (cases val
    [(ExprV expr env) (strict (eval expr env))]
    [else val]))

(: eval : SLOTH ENV -> VAL)
;; evaluates SLOTH expressions.
(define (eval expr env)
  ;; convenient helper
  (: eval* : SLOTH -> VAL)
  (define (eval* expr) (ExprV expr env))
  (cases expr
    [(Num n)  (RktV n)]
    [(Id name) (lookup name env)]
    [(Bind names exprs bound-body)
    (eval bound-body (extend names (map eval* exprs) env))]
    [(Fun names bound-body)
    (FunV names bound-body env)]
    [(Call fun-expr arg-exprs)
    (let ([fval (strict (eval* fun-expr))]
          [arg-vals (map eval* arg-exprs)])
      (cases fval
        [(PrimV proc) (proc arg-vals)]
        [(FunV names body fun-env)
          (eval body (extend names arg-vals fun-env))]
        [else (error 'eval "function call with a non-function: ~s"
                      fval)]))]
    [(If cond-expr then-expr else-expr)
    (eval* (if (cases (strict (eval* cond-expr))
                  [(RktV v) v] ; Racket value => use as boolean
                  [else #t])  ; other values are always true
              then-expr
              else-expr))]))

(: run : String -> Any)
;; evaluate a SLOTH program contained in a string
(define (run str)
  (let ([result (strict (eval (parse str) global-environment))])
    (cases result
      [(RktV v) v]
      [else (error 'run "evaluation returned a bad value: ~s"
                  result)])))

;;; ----------------------------------------------------------------
;;; Tests

(test (run "{{fun {x} {+ x 1}} 4}")
      => 5)
(test (run "{bind {{add3 {fun {x} {+ x 3}}}} {add3 1}}")
      => 4)
(test (run "{bind {{add3 {fun {x} {+ x 3}}}
                  {add1 {fun {x} {+ x 1}}}}
              {bind {{x 3}} {add1 {add3 x}}}}")
      => 7)
(test (run "{bind {{identity {fun {x} x}}
                  {foo {fun {x} {+ x 1}}}}
              {{identity foo} 123}}")
      => 124)
(test (run "{bind {{x 3}}
              {bind {{f {fun {y} {+ x y}}}}
                {bind {{x 5}}
                  {f 4}}}}")
      => 7)
(test (run "{{{fun {x} {x 1}}
              {fun {x} {fun {y} {+ x y}}}}
            123}")
      => 124)

;; More tests for complete coverage
(test (run "{bind x 5 x}")      =error> "bad `bind' syntax")
(test (run "{fun x x}")        =error> "bad `fun' syntax")
(test (run "{if x}")            =error> "bad `if' syntax")
(test (run "{}")                =error> "bad syntax")
(test (run "{bind {{x 5} {x 5}} x}") =error> "duplicate*bind*names")
(test (run "{fun {x x} x}")    =error> "duplicate*fun*names")
(test (run "{+ x 1}")          =error> "no binding for")
(test (run "{+ 1 {fun {x} x}}") =error> "bad input")
(test (run "{+ 1 {fun {x} x}}") =error> "bad input")
(test (run "{1 2}")            =error> "with a non-function")
(test (run "{{fun {x} x}}")    =error> "arity mismatch")
(test (run "{if {< 4 5} 6 7}")  => 6)
(test (run "{if {< 5 4} 6 7}")  => 7)
(test (run "{if + 6 7}")        => 6)
(test (run "{fun {x} x}")      =error> "returned a bad value")

;; Test laziness
(test (run "{{fun {x} 1} {/ 9 0}}") => 1)
(test (run "{{fun {x} 1} {{fun {x} {x x}} {fun {x} {x x}}}}") => 1)
(test (run "{bind {{x {{fun {x} {x x}} {fun {x} {x x}}}}} 1}") => 1)

;; Test lazy constructors
(test (run "{bind {{l {list 1 {/ 9 0} 3}}}
              {+ {first l} {first {rest {rest l}}}}}")
      => 4)

;;; ----------------------------------------------------------------

Implementing Call by NeedTuesday, November 13th

As we have seen, there are a number of advantages for lazy evaluation, but its main disadvantage is the fact that it is extremely inefficient, to the point of rendering lots of programs impractical, for example, in:

{bind {{x {+ 4 5}}}
  {bind {{y {+ x x}}}
    y}}

we end up adding 4 and 5 twice. In other words, we don’t suffer from textual redundancy (each expression is written once), but we don’t avoid dynamic redundancy. We can get it back by simply caching evaluation results, using a box that will be used to remember the results. The box will initially hold #f, and it will change to hold the VAL that results from evaluation:

(define-type VAL
  [RktV  Any]
  [FunV  (Listof Symbol) SLOTH ENV]
  [ExprV SLOTH ENV (Boxof (U #f VAL))] ;*** new: mutable cache field
  [PrimV ((Listof VAL) -> VAL)])

We need a utility function to create an evaluation promise, because when an ExprV is created, its initial cache box needs to be initialized.

(: eval-promise : SLOTH ENV -> VAL)
;; used instead of `eval' to create an evaluation promise
(define (eval-promise expr env)
  (ExprV expr env (box #f)))

(And note that Typed Racket needs to figure out that the #f in this definition has a type of (U #f VAL) and not just #f.)

This eval-promise is used instead of ExprV in eval. Finally, whenever we force such an ExprV promise, we need to check if it was already evaluated, otherwise force it and cache the result. This is simple to do since there is a single field that is used both as a flag and a cached value:

(: strict : VAL -> VAL)
;; forces a (possibly nested) ExprV promise, returns a VAL that is
;; not an ExprV
(define (strict val)
  (cases val
    [(ExprV expr env cache)
    (or (unbox cache)
        (let ([val* (strict (eval expr env))])
          (set-box! cache val*)
          val*))]
    [else val]))

But note that this makes using side-effects in our interpreter even more confusing. (It was true with call-by-name too.)

The resulting code follows.

;; A call-by-need version of the SLOTH interpreter

#lang pl

;;; ----------------------------------------------------------------
;;; Syntax

#| The BNF:
  <SLOTH> ::= <num>
            | <id>
            | { bind {{ <id> <SLOTH> } ... } <SLOTH> }
            | { fun { <id> ... } <SLOTH> }
            | { if <SLOTH> <SLOTH> <SLOTH> }
            | { <SLOTH> <SLOTH> ... }
|#

;; A matching abstract syntax tree datatype:
(define-type SLOTH
  [Num  Number]
  [Id  Symbol]
  [Bind (Listof Symbol) (Listof SLOTH) SLOTH]
  [Fun  (Listof Symbol) SLOTH]
  [Call SLOTH (Listof SLOTH)]
  [If  SLOTH SLOTH SLOTH])

(: unique-list? : (Listof Any) -> Boolean)
;; Tests whether a list is unique, guards Bind and Fun values.
(define (unique-list? xs)
  (or (null? xs)
      (and (not (member (first xs) (rest xs)))
          (unique-list? (rest xs)))))

(: parse-sexpr : Sexpr -> SLOTH)
;; parses s-expressions into SLOTHs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(cons 'bind more)
    (match sexpr
      [(list 'bind (list (list (symbol: names) (sexpr: nameds))
                          ...)
          body)
        (if (unique-list? names)
          (Bind names (map parse-sexpr nameds) (parse-sexpr body))
          (error 'parse-sexpr "duplicate `bind' names: ~s" names))]
      [else (error 'parse-sexpr "bad `bind' syntax in ~s" sexpr)])]
    [(cons 'fun more)
    (match sexpr
      [(list 'fun (list (symbol: names) ...) body)
        (if (unique-list? names)
          (Fun names (parse-sexpr body))
          (error 'parse-sexpr "duplicate `fun' names: ~s" names))]
      [else (error 'parse-sexpr "bad `fun' syntax in ~s" sexpr)])]
    [(cons 'if more)
    (match sexpr
      [(list 'if cond then else)
        (If (parse-sexpr cond)
            (parse-sexpr then)
            (parse-sexpr else))]
      [else (error 'parse-sexpr "bad `if' syntax in ~s" sexpr)])]
    [(list fun args ...) ; other lists are applications
    (Call (parse-sexpr fun)
          (map parse-sexpr args))]
    [else (error 'parse-sexpr "bad syntax in ~s" sexpr)]))

(: parse : String -> SLOTH)
;; Parses a string containing an SLOTH expression to a SLOTH AST.
(define (parse str)
  (parse-sexpr (string->sexpr str)))

;;; ----------------------------------------------------------------
;;; Values and environments

(define-type ENV
  [EmptyEnv]
  [FrameEnv FRAME ENV])

;; a frame is an association list of names and values.
(define-type FRAME = (Listof (List Symbol VAL)))

(define-type VAL
  [RktV  Any]
  [FunV  (Listof Symbol) SLOTH ENV]
  [ExprV SLOTH ENV (Boxof (U #f VAL))]
  [PrimV ((Listof VAL) -> VAL)])

(: extend : (Listof Symbol) (Listof VAL) ENV -> ENV)
;; extends an environment with a new frame.
(define (extend names values env)
  (if (= (length names) (length values))
    (FrameEnv (map (lambda ([name : Symbol] [val : VAL])
                    (list name val))
                  names values)
              env)
    (error 'extend "arity mismatch for names: ~s" names)))

(: lookup : Symbol ENV -> VAL)
;; lookup a symbol in an environment, frame by frame,
;; return its value or throw an error if it isn't bound
(define (lookup name env)
  (cases env
    [(EmptyEnv) (error 'lookup "no binding for ~s" name)]
    [(FrameEnv frame rest)
    (let ([cell (assq name frame)])
      (if cell
        (second cell)
        (lookup name rest)))]))

(: unwrap-rktv : VAL -> Any)
;; helper for `racket-func->prim-val': strict and unwrap a RktV
;; wrapper in preparation to be sent to the primitive function
(define (unwrap-rktv x)
  (let ([s (strict x)])
    (cases s
      [(RktV v) v]
      [else (error 'racket-func "bad input: ~s" s)])))

(: wrap-in-val : Any -> VAL)
;; helper that ensures a VAL output using RktV wrapper when needed,
;; but leaving as is otherwise
(define (wrap-in-val x)
  (if (VAL? x) x (RktV x)))

(: racket-func->prim-val : Function Boolean -> VAL)
;; converts a racket function to a primitive evaluator function
;; which is a PrimV holding a ((Listof VAL) -> VAL) function.
;; (the resulting function will use the list function as is,
;; and it is the list function's responsibility to throw an error
;; if it's given a bad number of arguments or bad input types.)
(define (racket-func->prim-val racket-func strict?)
  (define list-func (make-untyped-list-function racket-func))
  (PrimV (lambda (args)
          (let ([args (if strict? (map unwrap-rktv args) args)])
            (wrap-in-val (list-func args))))))

;; The global environment has a few primitives:
(: global-environment : ENV)
(define global-environment
  (FrameEnv (list (list '+ (racket-func->prim-val + #t))
                  (list '- (racket-func->prim-val - #t))
                  (list '* (racket-func->prim-val * #t))
                  (list '/ (racket-func->prim-val / #t))
                  (list '< (racket-func->prim-val < #t))
                  (list '> (racket-func->prim-val > #t))
                  (list '= (racket-func->prim-val = #t))
                  ;; note flags:
                  (list 'cons  (racket-func->prim-val cons  #f))
                  (list 'list  (racket-func->prim-val list  #f))
                  (list 'first (racket-func->prim-val first #t))
                  (list 'rest  (racket-func->prim-val rest  #t))
                  (list 'null? (racket-func->prim-val null? #t))
                  ;; values
                  (list 'true  (RktV #t))
                  (list 'false (RktV #f))
                  (list 'null  (RktV null)))
            (EmptyEnv)))

;;; ----------------------------------------------------------------
;;; Evaluation

(: eval-promise : SLOTH ENV -> VAL)
;; used instead of `eval' to create an evaluation promise
(define (eval-promise expr env)
  (ExprV expr env (box #f)))

(: strict : VAL -> VAL)
;; forces a (possibly nested) ExprV promise, returns a VAL that is
;; not an ExprV
(define (strict val)
  (cases val
    [(ExprV expr env cache)
    (or (unbox cache)
        (let ([val* (strict (eval expr env))])
          (set-box! cache val*)
          val*))]
    [else val]))

(: eval : SLOTH ENV -> VAL)
;; evaluates SLOTH expressions.
(define (eval expr env)
  ;; convenient helper
  (: eval* : SLOTH -> VAL)
  (define (eval* expr) (eval-promise expr env))
  (cases expr
    [(Num n)  (RktV n)]
    [(Id name) (lookup name env)]
    [(Bind names exprs bound-body)
    (eval bound-body (extend names (map eval* exprs) env))]
    [(Fun names bound-body)
    (FunV names bound-body env)]
    [(Call fun-expr arg-exprs)
    (let ([fval (strict (eval* fun-expr))]
          [arg-vals (map eval* arg-exprs)])
      (cases fval
        [(PrimV proc) (proc arg-vals)]
        [(FunV names body fun-env)
          (eval body (extend names arg-vals fun-env))]
        [else (error 'eval "function call with a non-function: ~s"
                      fval)]))]
    [(If cond-expr then-expr else-expr)
    (eval* (if (cases (strict (eval* cond-expr))
                  [(RktV v) v] ; Racket value => use as boolean
                  [else #t])  ; other values are always true
              then-expr
              else-expr))]))

(: run : String -> Any)
;; evaluate a SLOTH program contained in a string
(define (run str)
  (let ([result (strict (eval (parse str) global-environment))])
    (cases result
      [(RktV v) v]
      [else (error 'run "evaluation returned a bad value: ~s"
                  result)])))

;;; ----------------------------------------------------------------
;;; Tests

(test (run "{{fun {x} {+ x 1}} 4}")
      => 5)
(test (run "{bind {{add3 {fun {x} {+ x 3}}}} {add3 1}}")
      => 4)
(test (run "{bind {{add3 {fun {x} {+ x 3}}}
                  {add1 {fun {x} {+ x 1}}}}
              {bind {{x 3}} {add1 {add3 x}}}}")
      => 7)
(test (run "{bind {{identity {fun {x} x}}
                  {foo {fun {x} {+ x 1}}}}
              {{identity foo} 123}}")
      => 124)
(test (run "{bind {{x 3}}
              {bind {{f {fun {y} {+ x y}}}}
                {bind {{x 5}}
                  {f 4}}}}")
      => 7)
(test (run "{{{fun {x} {x 1}}
              {fun {x} {fun {y} {+ x y}}}}
            123}")
      => 124)

;; More tests for complete coverage
(test (run "{bind x 5 x}")      =error> "bad `bind' syntax")
(test (run "{fun x x}")        =error> "bad `fun' syntax")
(test (run "{if x}")            =error> "bad `if' syntax")
(test (run "{}")                =error> "bad syntax")
(test (run "{bind {{x 5} {x 5}} x}") =error> "duplicate*bind*names")
(test (run "{fun {x x} x}")    =error> "duplicate*fun*names")
(test (run "{+ x 1}")          =error> "no binding for")
(test (run "{+ 1 {fun {x} x}}") =error> "bad input")
(test (run "{+ 1 {fun {x} x}}") =error> "bad input")
(test (run "{1 2}")            =error> "with a non-function")
(test (run "{{fun {x} x}}")    =error> "arity mismatch")
(test (run "{if {< 4 5} 6 7}")  => 6)
(test (run "{if {< 5 4} 6 7}")  => 7)
(test (run "{if + 6 7}")        => 6)
(test (run "{fun {x} x}")      =error> "returned a bad value")

;; Test laziness
(test (run "{{fun {x} 1} {/ 9 0}}") => 1)
(test (run "{{fun {x} 1} {{fun {x} {x x}} {fun {x} {x x}}}}") => 1)
(test (run "{bind {{x {{fun {x} {x x}} {fun {x} {x x}}}}} 1}") => 1)

;; Test lazy constructors
(test (run "{bind {{l {list 1 {/ 9 0} 3}}}
              {+ {first l} {first {rest {rest l}}}}}")
      => 4)

;;; ----------------------------------------------------------------

Side Effects in a Lazy LanguageTuesday, November 13th

We’ve seen that a lazy language without the call-by-need optimization is too slow to be practical, but the optimization makes using side-effects extremely confusing. Specifically, when we deal with side-effects (I/O, mutation, errors, etc) the order of evaluation matters, but in our interpreter expressions are getting evaluated as needed. (Remember tracing the prime-numbers code in Lazy Racket — numbers are tested as needed, not in order.) If we can’t do these things, the question is whether there is any point in using a purely functional lazy language at all — since computer programs often interact with an imperative world.

There is a solution for this: the lazy language does not have any (sane) facilities for doing things (like printf that prints something in plain Racket), but it can use a data structure that describes such operations. For example, in Lazy Racket we cannot print stuff sanely using printf, but we can construct a string using format (which is just like printf, except that it returns the formatted string instead of printing it). So (assuming Racket syntax for simplicity), instead of:

(define (foo n)
  (printf "~s + 1 = ~s\n" n (+ n 1)))

we will write:

(define (foo n)
  (format "~s + 1 = ~s\n" n (+ n 1)))

and get back a string. We can now change the way that our interpreter deals with the output value that it receives after evaluating a lazy expression: if it receives a string, then it can take that string as denoting a request for printout, and simply print it. Such an evaluator will do the printout when the lazy evaluation is done, and everything works fine because we don’t try to use any side-effects in the lazy language — we just describe the desired side-effects, and constructing such a description does not require performing side-effects.

But this only solves printing a single string, and nothing else. If we want to print two strings, then the only thing we can do is concatenate the two strings — but that is not only inefficient, it cannot describe infinite output (since we will not be able to construct the infinite string in memory). So we need a better way to chain several printout representations. One way to do so is to use a list of strings, but to make things a little easier to manage, we will create a type for I/O descriptions — and populate it with one variant holding a string (for plain printout) and one for holding a chain of two descriptions (which can be used to construct an arbitrarily long sequence of descriptions):

(define-type IO
  [Print  String]
  [Begin2 IO IO])

Now we can use this to chain any number of printout representations by turning them into a single Begin2 request, which is very similar to simply using a loop to print the list. For example, the eager printout code:

(: print-list : (Listof A) -> Void)
(define (print-list l)
  (if (null? l)
    (printf "\n")
    (begin (printf "~s " (first l))
          (print-list (rest l)))))

turns to the following code:

(: print-list : (Listof A) -> IO)
(define (print-list l)
  (if (null? l)
    (Print "\n")
    (Begin2 (Print (format "~s " (first l)))
            (print-list (rest l)))))

This will basically scan an input list like the eager version, but instead of printing the list, it will convert it into a single output request that forms a recipe for this printout. Note that within the lazy world, the result of print-list is just a value, there are no side effects involved. Turning this value into the actual printout is something that needs to be done on the eager side, which must be part of the implementation. In the case of Lazy Racket, we have no access to the implementation, but we can do so in our Sloth implementation: again, run will inspect the result and either print a given string (if it gets a Print value), or print two things recursively (if it gets a Begin2 value). (To implement this, we will add an IOV variant to the VAL type definition, and have it contain an IO description of the above type.)

Because the sequence is constructed in the lazy world, it will not require allocating the whole sequence in memory — it can be forced bits by bits (using strict) as the imperative back-end (the run part of the implementation) follows the instructions in the resulting IO description. More concretely, it will also work on an infinite list: the translation of an infinite-loop printout function will be one that returns an infinite IO description tree of Begin2 values. This loop will also force only what it needs to print and will go on recursively printing the whole sequence (possibly not terminating). For example (again, using Racket syntax), the infinite printout loop

(: print-loop : -> Void)
(define (print-loop)
  (printf "foo\n")
  (print-loop))

is translated into a function that returns an infinite tree of print operations:

(: print-loop : -> IO)
(define (print-loop)
  (Begin2 (Print "foo\n")
          (print-loop)))

When this tree is converted to actions, it will result in an infinite loop that produces the same output — it is essentially the same infinite loop, only now it’s derived by an infinite description rather than an infinite process.

Finally, how should we deal with inputs? We can add another variant to our type definition that represents a read-line operation, assuming that like read-line it does not require any arguments:

(define-type IO
  [Print    String]
  [ReadLine ]
  [Begin2  IO IO])

Now the eager implementation can invoke read-line when it encounters a ReadLine value — but what should it do with the resulting string? Even worse, naively binding a value to ReadLine

(let ([name (ReadLine)])
  (Print (format "Your name is ~a" name)))

doesn’t get us the string that is read — instead, the value is a description of a read operation, which is very different from the actual string value that we want in the binding.

The solution is to take the “code that acts on the string value” and make it be the argument to ReadLine. In the above example, that could would be the let expression without the (ReadLine) part — and as you rememebr from the time we introduced fun into WAE, taking away a named expression from a binding expression leads to a function. With this in mind, it makes sense to make ReadLine take a function value that represents what to do in the future, once the reading is actually done.

(ReadLine (lambda (name)
            (Print (format "Your name is ~a" name))))

This receiver value is a kind of a continuation of the computation, provided as a callback value — it will get the string that was read on the terminal, and will return a new description of side-effects that represents the rest of the process:

(define-type IO
  [Print    String]
  [ReadLine (String -> IO)]
  [Begin2  IO IO])

Now, when the eager side sees a ReadLine value, it will read a line, and invoke the callback function with the string that it has read. By doing this, the control goes back to the lazy world to process the value and get back another IO value to continue the processing. This results in a process where the lazy code generates some IO descriptions, then the imperative side will execute it and control goes back to the lazy code, then back to the imperative side, etc.

As a more verbose example of all of the above, this silly loop:

(: silly-loop : -> Void)
(define (silly-loop)
  (printf "What is your name? ")
  (let ([name (read-line)])
    (if (equal? name "quit")
      (printf "bye\n")
      (begin (printf "Your name is ~s\n" name)
            (silly-loop)))))

is now translated to:

(: silly-loop : -> IO)
(define (silly-loop)
  (Begin2 (Print "What is your name? ")
          (ReadLine
          (lambda (name)
            (if (equal? name "quit")
              (Print "bye\n")
              (Begin2 (Print (format "Your name is ~s\n" name))
                      (silly-loop)))))))

Using this strategy to implement side-effects is possible, and you will do that in the homework — some technical details are going to be different but the principle is the same as discussed above. The last problem is that the above code is difficult to work with — in the homework you will see how to use syntactic abstractions to make thing much simpler.

Designing Domain Specific Languages (DSLs)Tuesday, November 13th

PLAI §35

Programming languages differ in numerous ways:

  1. Each uses different notations for writing down programs. As we’ve observed, however, syntax is only partially interesting. (This is, however, less true of languages that are trying to mirror the notation of a particular domain.)

  2. Control constructs: for instance, early languages didn’t even support recursion, while most modern languages still don’t have continuations.

  3. The kinds of data they support. Indeed, sophisticated languages like Racket blur the distinction between control and data by making fragments of control into data values (such as first-class functions and continuations).

  4. The means of organizing programs: do they have functions, modules, classes, namespaces, …?

  5. Automation such as memory management, run-time safety checks, and so on.

Each of these items suggests natural questions to ask when you design your own languages in particular domains.

Obviously, there are a lot of domain specific languages these days — and that’s not new. For example, four of the oldest languages were conceived as domain specific languages:

Only in the late 60s / early 70s languages began to get free from their special purpose domain and become general purpose languages (GPLs). These days, we usually use some GPL for our programs and often come up with small domain specific languages (DSLs) for specific jobs. The problem is designing such a specific language. There are lots of decisions to make, and as should be clear now, many ways of shooting your self in the foot. You need to know:

And very important:

To clarify why this can be applicable in more situations than you think, consider what programming languages are used for. One example that should not be ignored is using a programming language to implement a programming language — for example, what we did so far (or any other interpreter or compiler). In the same way that some piece of code in a PL represent functions about the “real world”, there are other programs that represent things in a language — possibly even the same one. To make a side-effect-full example, the meaning of one-brick might abstract over laying a brick when making a wall — it abstracts all the little details into a function:

(define (one-brick wall brick-pile)
  (move-eye (location brick-pile))
  (let ([pos (find-available-brick-position brick-pile)])
    (move-hand pos)
    (grab-object))
  (move-eye wall)
  (let ([pos (find-next-brick-position wall)])
    (move-hand pos)
    (drop-object)))

and we can now write

(one-brick my-wall my-brick-pile)

instead of all of the above. We might use that in a loop:

(define (build-wall wall pile)
  (define (loop n)
    (when (< n 500)
      (one-brick wall pile)
      (loop (add1 n))))
  (loop 0))

This is a common piece of looping code that we’ve seen in many forms, and a common complaint of newcomers to functional languages is the lack of some kind of a loop. But once you know the template, writing such loops is easy — and in fact, you can write code that would take something like:

(define (build-wall wall pile)
  (loop-for i from 1 to 500
    (one-brick wall pile)))

and produce the previous code. Note the main point here: we switch from code that deals with bricks to code that deals with code.

Now, a viable option for implementing a new DSL is to do so by transforming it into an existing language. Such a process is usually tedious and error prone — tedious because you need to deal with the boring parts of a language (making a parser etc), and error prone because it’s easy to generate bad code (especially when you’re dealing with strings) and you get bad errors in terms of the translated code instead of the actual code, resorting to debugging the intermediate generated programs. Lisp languages traditionally have taken this idea one level further than other languages: instead of writing a new transformer for your language, you use the host language, but you extend and customize it by adding you own forms.

Side-note: WSJ on the proliferation of PLsTuesday, November 13th

“Computer Languages Multiply, Pleasing Many–But Not All” Wall Street Journal (12/14/05) P. B1; Gomes, Lee

While the proliferation of languages has been a boon to software programmers, the extensive variety often frustrates their bosses and confounds the larger software companies. C and the subsequent C++ may be the most popular languages in use today, but any programmer working on the Web must also include languages such as Perl, Python, PHP, and TCL in his resume. The explosion has been partially fueled by the ability of an individual programmer or a small group to create and market a language, as was the case with Ruby on Rails, which became an overnight sensation thanks to a 15-minute demonstration video the Danish programmer David Hansson circulated over the Web. Once a language has gained a core following, blogs and Web sites appear to track its developments. Many languages owe their origins to small design firms trying to make a commercial success of themselves, while others are labors of love, as is the case with many open source projects. As new languages continue to emerge, however, more programmers are defecting from mainstream systems such as .NET and Java in favor of niche offerings that are more tailored to a specific project. CIOs are often assailed by complaints from their programmers when they try to impose restrictions on the number of languages that are permissible. While it has been demonstrated theoretically that each language is the rough equivalent of any other, it is no more likely for a consensus to appear within the programming community than it is for a single car to be met with a universal embrace from the entire fleet of motorists.

Syntax Transformations: MacrosTuesday, November 13th

PLAI §36

Macros are one of the biggest advantages of all Lisps, and specifically even more so an advantage of Scheme implementations, and yet more specifically, it is a major Racket feature: this section is therefore specific to Racket (which has this unique feature), although most of this is the same in most Schemes.

As we have previously seen, it is possible to implement one language construct using another. What we did could be described as bits of a compiler, since they translate one language to another.

We will see how this can be done in Racket: implementing some new linguistic forms in terms of ones that are already known. In essence, we will be translating Racket constructs to other Racket constructs — and all that is done in Racket, no need to go back to the language Racket was implemented in (C).

This is possible with a simple “trick”: the Racket implementation uses some syntax objects. These objects are implemented somehow inside Racket’s own source code. But these objects are also directly available for our use — part of the implementation is exposed to our level. This is quite similar to the way we have implemented pairs in our language — a TOY or a SLOTH pair is implemented using a Racket pair, so the same data object is available at both levels.

This is the big idea in Lisp, which Scheme (and therefore Racket) inherited from (to some extent): programs are made of numbers, strings, symbols and lists of these — and these are all used both at the meta-level as well as the user level. This means that instead of having no meta-language at all (locking away a lot of useful stuff), and instead of having some crippled half-baked meta language (CPP being both the most obvious (as well as the most popular) example for such a meta language), instead of all this we get exactly the same language at both levels.

How is this used? Well, the principle is simple. For example, say we want to write a macro that will evaluate two forms in sequence, but if the first one returns a result that is not false then it returns it instead of evaluating the second one too. This is exactly how or behaves, so pretend we don’t have it — call our version orelse:

(orelse <expr1> <expr2>)

in effect, we add a new special form to our language, with its own evaluation rule, only we know how to express this evaluation rule by translating it to things that are already part of our language.

We could do this as a simple function — only if we’re willing to explicitly delay the arguments with a lambda, and use the thunks in the function:

(define (orelse thunk1 thunk2)
  (if (thunk1)
    (thunk1) ; ignore the double evaluation for now
    (thunk2)))

or:

(define (orelse thunk1 thunk2)
  ((if (thunk1)
    thunk1
    thunk2)))

and using it like this:

(orelse (lambda () 1) (lambda () (error "boom")))

But this is clearly not the right way to do this: whoever uses this code must be aware of the need to send us thunks, and it’s verbose and inconvenient.

Note that this could be a feasible solution if there was a uniform way to have an easy syntactic way to say “a chunk of code” instead of immediately execute it — this is exactly what (lambda () ...) does. So we could, for example, make {...} be a shorthand for that, which is what Perl-6 is doing. However, we will soon see examples where we want more than just delay the evaluation of some code.

We want to translate

(orelse <expr1> <expr2>)

--to-->

(if <expr1>
  <expr1>
  <expr2>)

If we look at the code as an s-expression, then we can write the following function:

(define (translate-orelse l)
  (if (and (list? l)
          (= 3 (length l))
          (eq? 'orelse (first l)))
    (list 'if (second l) (second l) (third l))
    (error 'translate-orelse "bad input: ~s" l)))

We can now try it with a simple list:

(translate-orelse '(orelse foo1 foo2))

and note that the result is correct.

How is this used? Well, all we need is to hook our function into our implementation’s evaluator. In Lisp, we get a defmacro form for this, and many Schemes inherited it or something similar. In Racket, we need to

(require compatibility/defmacro)

but it requires the transformation to be a little different in a way that makes life easier: the above contains a lot of boilerplate code. Usually, we will require the input to be a list of some known length, the first element to be a symbol that specifies our form, and then do something with the other arguments. So we’d want to always follow a template that looks like:

(define (translate-??? exprs)
  (if (and (list? exprs)
          (= N (length exprs))
          (eq? '??? (car exprs)))
    (let ([E1 (cadr exprs)]
          [E2 (caddr exprs)]
          ...)
      ...make result expression...)
    (error ...)))

But this looks very similar to making sure that a function call is a specific function call (and for a good reason — macro usages look just like function calls). So make the translation function get a number of arguments one each for each part of the input, an s-expression. For example, the above translation and test become:

(define (translate-orelse <expr1> <expr2>)
  (list 'if <expr1> <expr1> <expr2>))

(translate-orelse 'foo1 'foo2)

The number of arguments is used to check the input (turning an arity error for the macro to an arity error for the translator function call), and we don’t need to “caddr our way” to arguments.

This gives us the simple definition — but what about the promised hook? — All we need is to use define-macro instead of define, and change the name to the name that will trigger this translation (providing the last missing test of the input):

(define-macro (orelse <expr1> <expr2>)
  (list 'if <expr1> <expr1> <expr2>))

and test it:

(orelse 1 (error "boom"))

Note that this is basically a (usually purely functional) lazy language of transformations which is built on top of Racket. It is possible for macros to generate pieces of code that contain references to these same macros, and they will be used to expand those instances again.

Now we start with the problems, one by one.

Macro ProblemsTuesday, November 13th

There is an inherent problem when macros are being used, in any form and any language (even in CPP): you must remember that you are playing with expressions, not with values — which is why this is problematic:

(define (foo x) (printf "foo ~s!\n" x) x)

(or (foo 1) (foo 2))

(orelse (foo 1) (foo 2))

And the reason for this should be clear. The standard solution for this is to save the value as a binding — so back to the drawing board, we want this transformation instead:

(orelse <expr1> <expr2>)
-->
(let ((val <expr1>))
  (if val
    val
    <expr2>))

(Note that we would have the same problem in the version that used simple functions and thunks.)

And to write the new code:

(define-macro (orelse <expr1> <expr2>)
  (list 'let (list (list 'val <expr1>))
    (list 'if 'val
      'val
      <expr2>)))

(orelse (foo 1) (foo 2))

and this works like we want it to.

Complexity of S-expression transformationsTuesday, November 13th

As can be seen, writing a simple macro doesn’t look too good — what if we want to write a more complicated macro? A solution to this is to look at the above macro and realize that it almost looks like the code we want — we basically want to return a list of a certain fixed shape, we just want some parts to be filled in by the given arguments. Something like:

(define-macro (orelse <expr1> <expr2>)
  '(let ((val <expr1>))
    (if val
      val
      <expr2>)))

if we had a way to make the <...>s not be a fixed part of the result, but we actually want the values that the transformation function received. (Remember that the < and > are just a part of the name, no magic, just something to make these names stand out.) This is related to notational problems that logicians and philosophers had problems with for centuries. One solution that Lisp uses for this is: instead of a quote, use backquote (called quasiquote in Racket) which is almost like quote, except that you can unquote parts of the value inside. This is done with a “,” comma. Using this, the above code can be written like this:

(define-macro (orelse <expr1> <expr2>)
  `(let ((val ,<expr1>))
    (if val
      val
      ,<expr2>)))

Scoping problemsTuesday, November 20th

You should be able to guess what’s this problem about. The basic problem of these macros is that they cannot be used reliably — the name that is produced by the macro can shadow a name that is in a completely different place, therefore destroying lexical scope. For example, in:

(let ((val 4))
  (orelse #f val))

the val in the macro shadows the use of this name in the above. One way to solve this is to write macros that look like this:

(define-macro (orelse <expr1> <expr2>)
  `(let ((%%!my*internal*var-do-not-use!%% ,<expr1>))
    (if %%!my*internal*var-do-not-use!%%
      %%!my*internal*var-do-not-use!%%
      ,<expr2>)))

or:

(define-macro (orelse <expr1> <expr2>)
  `(let ((i-am-using-orelse-so-i-should-not-use-this-name ,<expr1>))
    (if i-am-using-orelse-so-i-should-not-use-this-name
      i-am-using-orelse-so-i-should-not-use-this-name
      ,<expr2>)))

or (this is actually similar to using UUIDs):

(define-macro (orelse <expr1> <expr2>)
  `(let ((eli@barzilay.org/foo/bar/2002-02-02-10:22:22 ,<expr1>))
    (if eli@barzilay.org/foo/bar/2002-02-02-10:22:22
      eli@barzilay.org/foo/bar/2002-02-02-10:22:22
      ,<expr2>)))

Which is really not too good because such obscure variables tend to clobber each other too, in all kinds of unexpected ways.

Another way is to have a function that gives you a different variable name every time you call it:

(define-macro (orelse <expr1> <expr2>)
  (let ((temp (gensym)))
    `(let ((,temp ,<expr1>))
      (if ,temp
        ,temp
        ,<expr2>))))

but this is not safe either since there might still be clashes of these names (eg, if they’re using a counter that is specific to the current process, and you start a new process and load code that was generated earlier). The Lisp solution for this (which Racket’s gensym function implements as well) is to use uninterned symbols — symbols that have their own identity, much like strings, and even if two have the same name, they are not eq?.

Note also that there is the mirror side of this problem — what happens if we try this:

(let ([if 123]) (orelse #f #f))

? This leads to capture in the other direction — the code above shadows the if binding that the macro produces.

Some Schemes will allow something like

(define-macro (foo x)
  `(,mul-list ,x))

but this is a hack since the macro outputs something that is not a pure s-expression (and it cannot work for a syntactic keyword like if). Specifically, it is not possible to write the resulting expression (to a compiled file, for example).

We will ignore this for a moment.


Another problem — manageability of these transformations.

Quasiquotes gets us a long way, but it is still insufficient.

For example, lets write a Racket bind that uses lambda for binding. The transformation we now want is:

(bind ((var expr) ...)
  body)
-->
((lambda (var ...) body)
expr ...)

The code for this looks like this:

(define-macro (bind var-expr-list body)
  (cons (list 'lambda (map car var-expr-list) body)
        (map cadr var-expr-list)))

This already has a lot more pitfalls. There are lists and conses that you should be careful of, there are maps and there are cadrs that would be catastrophic if you use cars instead. The quasiquote syntax is a little more capable — you can write this:

(define-macro (bind var-expr-list body)
  `((lambda ,(map car var-expr-list) ,body)
    ,@(map cadr var-expr-list)))

where “,@” is similar to “,” but the unquoted expression should evaluate to a list that is spliced into its surrounding list (that is, its own parens are removed and it’s made into elements in the containing list). But this is still not as readable as the transformation you actually want, and worse, it is not checking that the input syntax is valid, which can lead to very confusing errors.

This is yet another problem — if there is an error in the resulting syntax, the error will be reported in terms of this result rather than the syntax of the code. There is no easy way to tell where these errors are coming from. For example, say that we make a common mistake: forget the “@” character in the above macro:

(define-macro (bind var-expr-list body)
  `((lambda ,(map car var-expr-list) ,body)
    ,(map cadr var-expr-list)))

Now, someone else (the client of this macro), tries to use it:

> (bind ((x 1) (y 2)) (+ x y))
procedure application: expected procedure,
given: 1; arguments were: 2

Yes? Now what? Debugging this is difficult, since in most cases it is not even clear that you were using a macro, and in any case the macro comes from code that you have no knowledge of and no control over. [The problem in this specific case is that the macro expands the code to:

((lambda (x y) (+ x y))
(1 2))

so Racket will to use 1 as a function and throw a runtime error.]

Adding error checking to the macro results in this code:

(define-macro (bind var-expr-list body)
  (if (andmap (lambda (var-expr)
                (and (list? var-expr)
                    (= 2 (length var-expr))
                    (symbol? (car var-expr))))
              var-expr-list)
    `((lambda ,(map car var-expr-list) ,body)
      ,@(map cadr var-expr-list))
    (error 'bind "bad syntax whaaaa!")))

Such checks are very important, yet writing this is extremely tedious.

Scheme (and Racket) MacrosTuesday, November 20th

Scheme, Racket included (and much extended), has a solution that is better than defmacro: it has define-syntax and syntax-rules. First of all, define-syntax is used to create the “magical connection” between user code and some macro transformation code that does some rewriting. This definition:

(define-syntax foo
  ...something...)

makes foo be a special syntax that, when used in the head of an expression, will lead to transforming the expression itself, where the result of this transformation is what gets used instead of the original expression. The “...something...” in this code fragment should be a transformation function — one that consumes the expression that is to be transformed, and returns the new expression to run.

Next, syntax-rules is used to create such a transformation in an easy way. The idea is that what we thought to be an informal specification of such rewrites, for example:

`let' can be defined as the following transformation:
  (let ((x v) ...) body ...)
  --> ((lambda (x ...) body ...) v ...)

and

`let*' is defined with two transformation rules:
1. (let* () body ...)
  --> (let () body ...)
2. (let* ((x1 v1) (x2 v2) ...) body ...)
  --> (let ((x1 v1)) (let* ((x2 v2) ...) body ...))

can actually be formalized by automatically creating a syntax transformation function from these rule specifications. (Note that this example has round parentheses so we don’t fall into the illusion that square brackets are different: the resulting transformation would be the same.) The main point is to view the left hand side as a pattern that can match some forms of syntax, and the right hand side as producing an output that can use some matched patterns.

syntax-rules is used with such rewrite specifications, and it produces the corresponding transformation function. For example, this:

(syntax-rules () ;*** ignore this "()" for now
  [(x y) (y x)])

evaluates to a function that is somewhat similar to:

(lambda (expr)
  (if (and (list? expr) (= 2 (length expr)))
    (list (second expr) (first expr))
    (error "bad syntax")))

but match is a little closer, since it uses similar input patterns:

(lambda (expr)
  (match expr
    [(list x y) (list y x)]
    [else (error "bad syntax")]))

Such transformations are used in a define-syntax expression to tie the transformer back into the compiler by hooking it on a specific keyword. You can now appreciate how all this work when you see how easy it is to define macros that are very tedious with define-macro. For example, the above bind:

(define-syntax bind
  (syntax-rules ()
    [(bind ((x v) ...) body ...)
    ((lambda (x ...) body ...) v ...)]))

and let* with its two rules:

(define-syntax let*
  (syntax-rules ()
    [(let* () body ...)
    (let () body ...)]
    [(let* ((x v) (xs vs) ...) body ...)
    (let ((x v)) (let* ((xs vs) ...) body ...))]))

These transformations are so convenient to follow, that Scheme specifications (and reference manuals) describe forms by specifying their definition. For example, the Scheme report, specifies let* as a “derived form”, and explains its semantics via this transformation.

The input patterns in these rules are similar to match patterns, and the output patterns assemble an s-expression using the matched parts in the input. For example:

(x y) --> (y x)

does the thing you expect it to do — matches a parenthesized form with two sub-forms, and produces a form with the two sub-forms swapped. The rules for “...” on the left side are similar to match, as we have seen many times, and on the right side it is used to splice a matched sequence into the resulting expression and it is required to use the ... for sequence-matched pattern variables. For example, here is a list of some patterns, and a description of how they match an input when used on the left side of a transformation rule and how they produce an output expression when they appear on the right side:

Some examples of transformations that would be very tedious to write code manually for:


This is solving the problems of easy code — no need for list, cons etc, not even for quasiquotes and tedious syntax massaging. But there were other problems. First, there was a problem of bad scope, one that was previously solved with a gensym:

(define-macro (orelse <expr1> <expr2>)
  (let ((temp (gensym)))
    `(let ((,temp ,<expr1>))
      (if ,temp ,temp ,<expr2>))))

Translating this to define-syntax and syntax-rules we get something simpler:

(define-syntax orelse
  (syntax-rules ()
    [(orelse <expr1> <expr2>)
    (let ((temp <expr1>))
      (if temp temp <expr2>))]))

Even simpler, Racket has a macro called define-syntax-rule that expands to a define-syntax combined with a syntax-rules — using it, we can write:

(define-syntax-rule (orelse <expr1> <expr2>)
  (let ((temp <expr1>))
    (if temp temp <expr2>)))

This looks like like a function — but you must remember that it is a transformation rule specification which is a very different beast, as we’ll see.

The main thing here is that Racket takes care of making bindings follow the lexical scope rules:

(let ([temp 4])
  (orelse #f temp))

works fine. In fact, it fully respects the scoping rules: there is no confusion between bindings that the macro introduces and bindings that are introduced where the macro is used. (Think about different colors for bindings introduced by the macro and other bindings.) It’s fine with many cases that are much harder to cope with otherwise (eg, cases where there is no gensym magic solution):

(let ([if +])
  (orelse 1 1))

(let ([if +])
  (if (orelse 1 1) 10 100)) ; two different `if's here

You can even use both:

(let ([if #f] [temp 4])
  (orelse if temp))

and use DrRacket’s macro debugger to see how the various bindings get colored differently.

define-macro advocates will claim that it is difficult to make a macro that intentionally plants an identifier. Think about a loop macro that has an abort that can be used inside its body. Or an if-it form that is like if, but makes it possible to use the condition’s value in the “then” branch as an it binding. It is possible with all Scheme macro systems to “break hygiene” in such ways, and we will later see how to do this in Racket. However, Racket also provides a better way to deal with such problems (think about it being always “bound to a syntax error”, but locally rebound in an if-it form).

Scheme macros are said to be hygienic — a term used to specify that they respect lexical scope. (All of this can get much more important in the presence of a module system, since you can write a module that provides transformations rules, not just values and functions.) There are several implementations of hygienic macro systems across Scheme implementations.


The way that Scheme implementations achieve hygiene in a macro system is by making it deal with more than just raw S-expressions. Roughly speaking, it deals with syntax objects that are sort of a wrapper structure around S-expression, carrying additional information. The important part of this information when it gets to dealing with hygiene is the “lexical scope” — which can roughly be described as having identifiers be represented as symbols plus a “color” which represents the scope. This way such systems can properly avoid confusing identifiers with the same name that come from different scopes.

There was also the problem of making debugging difficult, because a macro can introduce errors that are “coming out of nowhere”. In the implementation that we work with, this is solved by adding yet more information to these syntax objects — in addition to the underlying S-expression and the lexical scope, they also contain source location information. This allows Racket (and DrRacket) to locate the source of a specific syntax error, so locating the offending code is easy. DrRacket’s macro debugger heavily relies on this information to provide a very useful tool — since writing macros can easily become a hard job.

Finally, there was the problem of writing bad macros. For example, it is easy to forget that you’re dealing with a macro definition and write:

(define-syntax-rule (twice x) (+ x x))

just because you want to inline the addition — but in this case you end up duplicating the input expression which can have a disastrous effect. For example:

(twice (twice (twice (twice (twice (twice (twice (twice 1))))))))

expands to a lot of code to compile.

Another example is:

(define-syntax-rule (with-increment var expr)
  (let ([var (add1 var)]) expr))
...
(with-increment (* foo 2)
  ...code...)

the problem here is that (* foo 2) will be used as an identifier to be bound by the let expression — which can lead to a confusing syntax error.

Racket provides many tools to help macro programmers — in addition to a user-interface tool like the macro debugger there are also programmer-level tools where you can reject an input if it doesn’t contain an identifier at a certain place etc. Still, writing macros is much harder than writing functions — some of these problems are inherent to the problem that macros solve; for example, you may want a twice macro that replicates an expression. By specifying a transformation to the core language, a macro writer has full control over which expressions get evaluated and how, which identifiers are binding instances, and how is the scope of the given expression is shaped.

Meta MacrosTuesday, November 20th

One of the nice results of syntax-rules dealing with the subtle points of identifiers and scope is that things works fine even when we “go up a level”. For example, the short define-syntax-rule form that we’ve seen is itself a defined as a simple macro:

(define-syntax define-syntax-rule
  (syntax-rules ()
    [(define-syntax-rule (name P ...) B)
    (define-syntax name
      (syntax-rules ()
        [(name P ...) B]))]))

In fact, this is very similar to something that we have already seen: the rewrite form that we have used in Schlac is implemented in just this way. The only difference is that rewrite requires an actual => token to separate the input pattern from the output template. If we just use it in a syntax rule:

(define-syntax rewrite
  (syntax-rules ()
    [(rewrite (name P ...) => B)
    (define-syntax name
      (syntax-rules ()
        [(name P ...) B]))]))

it won’t work. Racket treats the above => just like any identifier, which in this case acts as a pattern variable which matches anything. The solution to this is to list the => as a keyword which is expected to appear in the macro use as-is — and that’s what the mysterious () of syntax-rules is used for: any identifier listed there is taken to be such a keyword. This makes the following version

(define-syntax rewrite
  (syntax-rules (=>)
    [(rewrite (name P ...) => B)
    (define-syntax name
      (syntax-rules ()
        [(name P ...) B]))]))

do what we want and throw a syntax error unless rewrite is used with an actual => in the proper place.

Lazy Constructions in an Eager LanguageTuesday, November 20th

PLAI §37 (has some examples)

This is not really lazy evaluation, but it gets close, and provides the core useful property of easy-to-use infinite lists.

(define-syntax-rule (cons-stream x y)
  (cons x (lambda () y)))
(define stream? pair?)
(define null-stream null)
(define null-stream? null?)
(define stream-first first)
(define (stream-rest s) ((rest s)))

Using it:

(define ones (cons-stream 1 ones))
(define (stream-map f s)
  (if (null-stream? s)
    null-stream
    (cons-stream (f (stream-first s))
                (stream-map f (stream-rest s)))))
(define (stream-map2 f s1 s2)
  (if (null-stream? s1)
    null-stream
    (cons-stream (f (stream-first s1) (stream-first s2))
                (stream-map2 f (stream-rest s1)
                                (stream-rest s2)))))
(define ints (cons-stream 0 (stream-map2 + ones ints)))

Actually, all Scheme implementations come with a generalized tool for (local) laziness: a delay form that delays computation of its body expression, and a force function that forces such promises. Here is a naive implementation of this:

(define-type promise
  [make-promise (-> Any)])

(define-syntax-rule (delay expr)
  (make-promise (lambda () expr)))

(define (force p)
  (cases p [(make-promise thunk) (thunk)]))

Proper definitions of delay/force cache the result — and practical ones can get pretty complex, for example, in order to allow tail calls via promises.

Recursive MacrosTuesday, November 20th

Syntax transformations can be recursive. For example, we have seen how let* can be implemented by a transformation that uses two rules, one of which expands to another use of let*:

(define-syntax let*
  (syntax-rules ()
    [(let* () body ...)
    (let () body ...)]
    [(let* ((x v) (xs vs) ...) body ...)
    (let ((x v)) (let* ((xs vs) ...) body ...))]))

When Racket expands a let* expression, the result may contain a new let* which needs extending as well. An important implication of this is that recursive macros are fine, as long as the recursive case is using a smaller expression. This is just like any form of recursion (or loop), where you need to be looping over a well-founded set of values — where each iteration uses a new value that is closer to some base case.

For example, consider the following macro:

(define-syntax-rule (while condition body ...)
  (when condition
    body ...
    (while condition body ...)))

It seems like this is a good implementation of a while loop — after all, if you were to implement it as a function using thunks, you’d write very similar code:

(define (while condition-thunk body-thunk)
  (when (condition-thunk)
    (body-thunk)
    (while condition-thunk body-thunk)))

But if you look at the nested while form in the transformation rule, you’ll see that it is exactly the same as the input form. This means that this macro can never be completely expanded — it specifies infinite code! In practice, this makes the (Racket) compiler loop forever, consuming more and more memory. This is unlike, for example, the recursive let* rule which uses one less binding-value pair than specified as its input.

The reason that the function version of while is fine is that it iterates using the same code, and the condition thunk will depend on some state that converges to a base case (usually the body thunk will perform some side-effects that makes the loop converge). But in the macro case there is no evaluation happening, if the transformed syntax contains the same input pattern, we end up having a macro that expands infinitely.

The correct solution for a while macro is therefore to use plain recursion using a local recursive function:

(define-syntax-rule (while condition body ...)
  (letrec ([loop (lambda ()
                  (when condition
                    body ...
                    (loop)))])
    (loop)))

A popular way to deal with macros like this that revolve around a specific control flow is to separate them into a function that uses thunks, and a macro that does nothing except wrap input expressions as thunks. In this case, we get this solution:

(define (while/proc condition-thunk body-thunk)
  (when (condition-thunk)
    (body-thunk)
    (while/proc condition-thunk body-thunk)))

(define-syntax-rule (while condition body ...)
  (while/proc (lambda () condition)
              (lambda () body ...)))

Another example: a simple loop.Tuesday, November 20th

Here is an implementation of a macro that does a simple arithmetic loop:

(define-syntax for
  (syntax-rules (= to do)
    [(for x = m to n do body ...)
    (letrec ([loop (lambda (x)
                      (when (<= x n)
                        body ...
                        (loop (+ x 1))))])
      (loop m))]))

(Note that this is not complete code: it suffers from the usual problem of multiple evaluations of the n expression. We’ll deal with it soon.)

This macro combines both control flow and lexical scope. Control flow is specified by the loop (done, as usual in Racket, as a tail-recursive function) — for example, it determines how code is iterated, and it also determines what the for form will evaluate to (it evaluates to whatever when evaluates to, the void value in this case). Scope is also specified here, by translating the code to a function — this code makes x have a scope that covers the body so this is valid:

(for i = 1 to 3 do (printf "i = ~s\n" i))

but it also makes the boundary expression n be in this scope, making this:

(for i = 1 to (if (even? i) 10 20) do (printf "i = ~s\n" i))

valid. In addition, while evaluating the condition on each iteration might be desirable, in most cases it’s not — consider this example:

(for i = 1 to (read) do (printf "i = ~s\n" i))

This is easily solved by using a let to make the expression evaluate just once:

(define-syntax for
  (syntax-rules (= to do)
    [(for x = m to n do body ...)
    (let ([n* n]
          [m* m]) ; execution order
      (letrec ([loop (lambda (x)
                        (when (<= x n*)
                          body ...
                          (loop (+ x 1))))])
        (loop m*)))]))

which makes the previous use result in a “reference to undefined identifier: i” error.

Furthermore, the fact that we have a hygienic macro system means that it is perfectly fine to use nested for expressions:

(for a = 1 to 9 do
  (for b = 1 to 9 do (printf "~s,~s " a b))
  (newline))

The transformation is, therefore, completely specifying the semantics of this new form.

Extending this syntax is easy using multiple transformation rules — for example, say that we want to extend it to have a step optional keyword. The standard idiom is to have the step-less pattern translated into one that uses step 1:

(for x = m to n do body ...)
--> (for x = m to n step 1 do body ...)

Usually, you should remember that syntax-rules tries the patterns one by one until a match is found, but in this case there is no problems because the keywords make the choice unambiguous:

(define-syntax for
  (syntax-rules (= to do step)
    [(for x = m to n do body ...)
    (for x = m to n step 1 do body ...)]
    [(for x = m to n step d do body ...)
    (let ([n* n]
          [m* m]
          [d* d])
      (letrec ([loop (lambda (x)
                        (when (<= x n*)
                          body ...
                          (loop (+ x d*))))])
        (loop m*)))]))

(for i = 1 to 10 do (printf "i = ~s\n" i))
(for i = 1 to 10 step 2 do (printf "i = ~s\n" i))

We can even extend it to do a different kind of iteration, for example, iterate over list:

(define-syntax for
  (syntax-rules (= to do step in)
    [(for x = m to n do body ...)
    (for x = m to n step 1 do body ...)]
    [(for x = m to n step d do body ...)
    (let ([n* n]
          [m* m]
          [d* d])
      (letrec ([loop (lambda (x)
                        (when (<= x n*)
                          body ...
                          (loop (+ x d*))))])
        (loop m*)))]
    ;; list
    [(for x in l do body ...)
    (for-each (lambda (x) body ...) l)]))

(for i in (list 1 2 3 4) do (printf "i = ~s\n" i))

(for i in (list 1 2 3 4) do
  (for i = 0 to i do (printf "i = ~s  " i))
  (newline))

Problems of syntax-rules MacrosTuesday, November 20th

As we’ve seen, using syntax-rules solves many of the problems of macros, but it comes with a high price tag: the macros are “just” rewrite rules. As rewrite rules they’re pretty sophisticated, but it still loses a huge advantage of what we had with define-macro — the macro code is no longer Racket code but a simple language of rewrite rules.

There are two big problems with this which we will look into now. (DrRacket’s macro stepper tool can be very useful in clarifying these examples.) The first problem is that in some cases we want to perform computations at the macro level — for example, consider a repeat macro that needs to expand like this:

(repeat 1 E)  -->  (begin E)
(repeat 2 E)  -->  (begin E E)
(repeat 3 E)  -->  (begin E E E)
...

With a syntax-rules macro we can match over specific integers, but we just cannot do this with any integer. Note that this specific case can be done better via a function — better by not replicating the expression:

(define (repeat/proc n thunk)
  (when (> n 0) (thunk) (repeat/proc (sub1 n) thunk)))
(define-syntax-rule (repeat N E)
  (repeat/proc N (lambda () E)))

or even better, assuming the above for is already implemented:

(define-syntax-rule (repeat N E)
  (for i = 1 to N do E))

But still, we want to have the ability to do such computation. A similar, and perhaps better example, is better error reporting. For example, the above for implementation blindly expands its input, so:

> (for 1 = 1 to 3 do (printf "i = ~s\n" i))
lambda: not an identifier in: 1

we get a bad error message in terms of lambda, which is breaking abstraction (it comes from the expansion of for, which is an implementation detail), and worse — it is an error about something that the user didn’t write.

Yet another aspect of this problem is that sometimes we need to get creative solutions where it would be very simple to write the corresponding Racket code. For example, consider the problem of writing a rev-app macro — (rev-app F E …) should evaluate to a function similar to (F E …), except that we want the evaluation to go from right to left instead of the usual left-to-right that Racket does. This code is obviously very broken:

(define-syntax-rule (rev-app F E ...)
  (let (reverse ([x E] ...))
    (F x ...)))

because it generates a malformed let form — there is no way for the macro expander to somehow know that the reverse should happen at the transformation level. In this case, we can actually solve this using a helper macro to do the reversing:

(define-syntax-rule (rev-app F E ...)
  (rev-app-helper F (E ...) ()))
(define-syntax rev-app-helper
  (syntax-rules ()
    ;; this rule does the reversing, collecting the reversed
    ;; sequence in the last part
    [(rev-app-helper F (E0 E ...) (E* ...))
    (rev-app-helper F (E ...) (E0 E* ...))]
    ;; and this rule fires up when we're done with the reversal
    [(rev-app-helper F () (E ...))
    (let ([x E] ...)
      (F x ...))]))

There are still problems with this — it complains about x ... because there is a single x there rather than a sequence of them; and even if it did somehow work, we also need the xs in that last line in the original order rather than the reversed one. So the solution is complicated by collecting new xs while reversing — and since we need them in both orders, we’re going to collect both orders:

(define-syntax-rule (rev-app F E ...)
  (rev-app-helper F (E ...) () () ()))
(define-syntax rev-app-helper
  (syntax-rules ()
    ;; this rule does the reversing, collecting the reversed
    ;; sequence in the last part -- also make up new identifiers
    ;; and collect them in *both* directions (`X' is the straight
    ;; sequence of identifiers, `X*' is the reversed one, and `E*'
    ;; is the reversed expression sequence); note that each
    ;; iteration introduces a new identifier called `t'
    [(rev-app-helper F (E0 E ...) (X ...  ) (  X* ...) (  E* ...))
    (rev-app-helper F (  E ...) (X ... t) (t X* ...) (E0 E* ...))]
    ;; and this rule fires up when we're done with the reversal and
    ;; the generation
    [(rev-app-helper F () (x ...) (x* ...) (E* ...))
    (let ([x* E*] ...)
      (F x ...))]))

;; see that it works
(define (show x) (printf ">>> ~s\n" x) x)
(rev-app list (show 1) (show 2) (show 3))

So, this worked, but in this case the simplicity of the syntax-rules rewrite language worked against us, and made a very inconvenient solution. This could have been much easier if we could just write a “meta-level” reverse, and a use of map to generate the names.

… And all of that was just the first problem. The second one is even harder: syntax-rules is designed to avoid all name captures, but what if we want to break hygiene? There are some cases where you want a macro that “injects” a user-visible identifier into its result. The most common (and therefore the classic) example of this is an anaphoric if macro, that binds it to the result of the test (which can be any value, not just a boolean):

;; find the element of `l' that is immediately following `x'
;; (assumes that if `x' is found, it is not the last one)
(define (after x l)
  (let ([m (member x l)])
    (if m
      (second m)
      (error 'after "~s not found in ~s" x l))))

which we want to turn to:

;; find the element of `l' that is immediately following `x'
;; (assumes that if `x' is found, it is not the last one)
(define (after x l)
  (if (member x l)
    (second it)
    (error 'after "~s not found in ~s" x l)))

The obvious definition of `if-it’ doesn’t work:

(define-syntax-rule (if-it E1 E2 E3)
  (let ([it E1]) (if it E2 E3)))

The reason it doesn’t work should be obvious now — it is designed to avoid the it that the macro introduced from interfering with the it that the user code uses.

Next, we’ll see Racket’s “low level” macro system, which can later be used to solve these problems.

Racket’s “Low-Level” MacrosTuesday, November 20th

As we’ve previously seen, syntax-rules creates transformation functions — but there are other more direct ways to write these functions. These involve writing a function directly rather than creating one with syntax-rules — and because this is a more low-level approach than using syntax-rules to generate a transformer, it is called a “low level macro system”. All Scheme implementations have such low-level systems, and these systems vary from one to the other. They all involve some particular type that is used as “syntax” — this type is always related to S-expressions, but it cannot be the simple define-macro tool that we’ve seen earlier if we want to avoid the problems of capturing identifiers.

Historical note: For a very long time the Scheme standard had avoided a concrete specification of this low-level system, leaving syntax-rules as the only way to write portable Scheme code. This had lead some people to explore more thoroughly the things that can be done with just syntax-rules rewrites, even beyond the examples we’ve seen. As it turns out, there’s a lot that can be done with it — in fact, it is possible to write rewrite rules that implement a lambda calculus, making it possible to write things that look close to “real code”. This is, however, awkward to get used to, and redundant with a macro system that can use the full language for arbitrary computations. It has also became less popular recently, since R6RS dictates something that is known as a “syntax-case macro system” (not really a good name, since syntax-case is just a tool in this system).

Racket uses an extended version of this syntax-case system, which is what we will discuss now. In the Racket macro system, “syntax” is a new type, not just S-expressions as is the case with define-macro. The way to think about this type is as a wrapper around S-expressions, where the S-expression is the “raw” symbolic form of the syntax, and a bunch of “stuff” is added. Two important bits of this “stuff” are the source location information for the syntax, and its lexical scope. The source location is what you’d expect: the file name for the syntax (if it was read from a file), its position in the file, and its line and column numbers; this information is mostly useful for reporting errors. The lexical scope information is used in a somewhat peculiar way: there is no direct way to access it, since usually you don’t need to do so — instead, for the rare cases where you do need to manipulate it, you copy the lexical scope of an existing syntax to create another. This allows the macro interface to be usable without specification of a specific representation for the scope.

The main piece of functionality in this system is syntax-case (which has lead to its common name) — a form that is used to deconstruct the input via pattern-matching similar to syntax-rules. In fact, the syntax of syntax-case looks very similar to the syntax of syntax-rules — there are zero or more parenthesized keywords, and then clauses that begin with the same kind of patterns to match the syntax against. The first obvious difference is that the syntax to be matched is given explicitly:

(syntax-case <value-to-match> (<keywords>)
  [<pattern> <result>]
  ...)

A macro is written as a plain function, usually used as the value in a define-syntax form (but it could also be used in plain helper functions). For example, here’s how the orelse macro is written using this:

(define-syntax orelse
  (lambda (stx)
    (syntax-case stx ()
      [(orelse x y) ???])))

Racket’s define-syntax can also use the same syntactic sugar for functions as define:

(define-syntax (orelse stx)
  (syntax-case stx ()
    [(orelse x y) ???]))

The second significant change from syntax-rules is that the right-hand-side expressions in the branches are not patterns. Instead, they’re plain Racket expressions. In this example (as in most uses of syntax-case) the result of the syntax-case form is going to be the result of the macro, and therefore it should return a piece of syntax. So far, the only piece of syntax that we see in this code is just the input stx — and returning that will get the macro expander in an infinite loop (because we’re essentially making a transformer for orelse expressions that expands the syntax to itself).

To return a new piece of syntax, we need a way to write new syntax values. The common way to do this is using a new special form: syntax. This form is similar to quote — except that instead of an S-expression, it results in a syntax. For example, in this code:

(define-syntax (orelse stx)
  (printf "Expanding ~s\n" stx)
  (syntax-case stx ()
    [(orelse x y) (syntax (printf "Running an orelse\n"))]))

the first printout happens during macro expansion, and the second is part of the generated code. Like quote, syntax has a convenient abbreviation — “#'”:

(define-syntax (orelse stx)
  (printf "Expanding ~s\n" stx)
  (syntax-case stx ()
    [(orelse x y) #'(printf "Running an orelse\n")]))

Now the question is how we can get the actual macro working. The thing is that syntax is not completely quoting its contents as a syntax — there could be some meta identifiers that are bound as “pattern variables” in the syntax-case pattern that was matched for the current clause — in this case, we have x and y as such pattern variables. (Actually, orelse is a pattern variable too, but this doesn’t matter for our purpose.) Using these inside a syntax will have them replaced by the syntax that they matched against. The complete orelse definition is therefore very easy:

(define-syntax (orelse stx)
  (syntax-case stx ()
    [(orelse <expr1> <expr2>)
    #'(let ((temp <expr1>))
        (if temp temp <expr2>))]))

The same treatment of ... holds here too — in the matching pattern they specify 0 or more occurrences of the preceding pattern, and in the output template they mean that the matching sequence is “spliced” in. Note that syntax-rules is now easy to define as a macro that expands to a function that uses syntax-case to do the actual rewrite work:

(define-syntax (syntax-rules stx)
  (syntax-case stx ()
    [(syntax-rules (keyword ...)
      [pattern template]
      ...)
    #'(lambda (stx)
        (syntax-case stx (keyword ...)
          [pattern #'template]
          ...))]))

Solving the syntax-rules problemsTuesday, November 20th

So far it looks like we didn’t do anything new, but the important change is already in: the fact that the results of a macro is a plain Racket expression mean that we can now add more API functionality for dealing with syntax values. There is no longer a problem with running “meta-level” code vs generated runtime code: anything that is inside a syntax (anything that is quoted with a “#'”) is generated code, and the rest is code that is executed when the macro expands. We will now introduce some of the Racket macro API by demonstrating the solutions to the syntax-rules problem that were mentioned earlier.

First of all, we’ve talked about the problem of reporting good errors. For example, make this:

(for 1 = 1 to 3 do ...)

throw a proper error instead of leaving it for lambda to complain about. To make it easier to play with, we’ll use a simpler macro:

(define-syntax fun
  (syntax-rules (->)
    [(_ id -> E) (lambda (id) E)])) ; _ matches the head `fun'

and using an explicit function:

(define-syntax (fun stx)
  (syntax-case stx (->)
    [(_ id -> E) #'(lambda (id) E)]))

One of the basic API functions is syntax-e — it takes in a syntax value and returns the S-expression that it wraps. In this case, we can pull out the identifier from this, and check that it is a valid identifier using symbol? on what it wraps:

(define-syntax (fun stx)
  (syntax-case stx (->)
    [(_ id -> E)
    (if (symbol? (syntax-e (cadr (syntax-e stx))))
      #'(lambda (id) E)
      (error 'fun "bad syntax: expecting an identifier, got ~s"
                  (cadr (syntax-e stx))))]))

The error is awkward though — it doesn’t look like the usual kind of syntax errors that Racket throws: it’s shown in an ugly way, and its source is not properly highlighted. A better way to do this is to use `raise-syntax-error’ — it takes an error message, the offending syntax, and the offending part of this syntax:

(define-syntax (fun stx)
  (syntax-case stx (->)
    [(_ id -> E)
    (if (symbol? (syntax-e (cadr (syntax-e stx))))
      #'(lambda (id) E)
      (raise-syntax-error
        'fun "bad syntax: expecting an identifier"
        stx (cadr (syntax-e stx))))]))

Another inconvenient issue is with pulling out the identifier. Consider that #'(lambda (id) E) is a new piece of syntax that has the supposed identifier in it — we pull it from that instead of from stx, but it would be even easier with #'(id), and even easier than that with just #'id which will be just the identifier:

(define-syntax (fun stx)
  (syntax-case stx (->)
    [(_ id -> E)
    (if (symbol? (syntax-e #'id))
      #'(lambda (id) E)
      (raise-syntax-error
        'fun "bad syntax: expecting an identifier"
        stx #'id))]))

Also, checking that something is an identifier is common enough that there is another predicate for this (the combination of syntax-e and symbol?) — identifier?:

(define-syntax (fun stx)
  (syntax-case stx (->)
    [(_ id -> E)
    (if (identifier? #'id)
      #'(lambda (id) E)
      (raise-syntax-error
        'fun "bad syntax: expecting an identifier"
        stx #'id))]))

As a side note, checking the input pattern for validity is very common, and in some cases might be needed to discriminate patterns (eg, one result when id is an identifier, another when it’s not). For this, syntax-cases clauses have “guard expressions” — so we can write the above more simply as:

(define-syntax (fun stx)
  (syntax-case stx (->)
    [(_ id -> E)
    (identifier? #'id)
    #'(lambda (id) E)]))

This, however, produces a less informative “bad syntax” error, since there is no way to tell what the error message should be. (There is a relatively new Racket tool called syntax-parse where such requirements can be specified and a proper error message is generated on bad inputs.)

We can now resolve the repeat problem — create a (repeat N E) macro:

(define-syntax (repeat stx)
  (define (n-copies n expr)
    (if (> n 0) (cons expr (n-copies (sub1 n) expr)) null))
  (syntax-case stx ()
    [(_ N E)
    (integer? (syntax-e #'N))
    #'(begin (n-copies (syntax-e #'N) #'E))]))

(Note that we can define an internal helper function, just like we do with plain functions.) But this doesn’t quite work (and if you try it, you’ll see an interesting error message) — the problem is that we’re generating code with a call to n-copies in it, instead of actually calling it. The problem is that we need to take the list that n-copies generates, and somehow “plant” it in the resulting syntax. So far the only things that were planted in it are pattern variables — and we can actually use another syntax-case to do just that: match the result of n-copies against a pattern variable, and then use that variable in the final syntax:

(define-syntax (repeat stx)
  (define (n-copies n expr)
    (if (> n 0) (cons expr (n-copies (sub1 n) expr)) null))
  (syntax-case stx ()
    [(_ N E)
    (number? (syntax-e #'N))
    (syntax-case (n-copies (syntax-e #'N) #'E) ()
      [(expr ...) #'(begin expr ...)])]))

This works — but one thing to note here is that n-copies returns a list, not a syntax. The thing is that syntax-case will automatically “coerce” S-expressions into a syntax in some way, easy to do in this case since we only care about the elements of the list, and those are all syntaxes.

However, this use of syntax-case as a pattern variable binder is rather indirect, enough that it’s hard to read the code. Since this is a common use case, there is a shorthand for that too: with-syntax. It looks as a kind of a let-like form, but instead of binding plain identifiers, it binds pattern identifiers — and in fact, the things to be bound are themselves patterns:

(define-syntax (repeat stx)
  (define (n-copies n expr)
    (if (> n 0) (cons expr (n-copies (sub1 n) expr)) null))
  (syntax-case stx ()
    [(_ N E)
    (number? (syntax-e #'N))
    (with-syntax ([(expr ...) (n-copies (syntax-e #'N) #'E)])
      #'(begin expr ...))]))

Note that there is no need to implement with-syntax as a primitive form — it is not too hard to implement it as a macro that expands to the actual use of syntax-case. (In fact, you can probably guess now that the Racket core language is much smaller than it seems, with large parts that are implemented as layers of macros.)

There is one more related group of shorthands that is relevant here: quasisyntax, unsyntax, and unsyntax-splicing. These are analogous to the quoting forms by the same names, and they have similar shorthands: “#`”, “#,” and “#,@”. They could be used to implement this macro:

(define-syntax (repeat stx)
  (define (n-copies n expr)
    (if (> n 0) (cons expr (n-copies (sub1 n) expr)) null))
  (syntax-case stx ()
    [(_ N E)
    (number? (syntax-e #'N))
    #`(begin #,@(n-copies (syntax-e #'N) #'E))]))

[As you might suspect now, these new forms are also implemented as macros, which expand to the corresponding uses of with-syntax, which in turn expand into syntax-case forms.]

We now have almost enough machinery to implement the rev-app macro, and compare it to the original (complex) version that used syntax-rules. The only thing that is missing is a way to generate a number of new identifiers — which we achieved earlier by a number of macro expansion (each expansion of a macro that has a new identifier x will have this identifier different from other expansions, which is why it worked). Racket has a function for this: generate-temporaries. Since it is common to generate temporaries for input syntaxes, the function expects an input syntax that has a list as its S-expression form (or a plain list).

(define-syntax (rev-app stx)
  (syntax-case stx ()
    [(_ F E ...)
    (let ([temps (generate-temporaries #'(E ...))])
      (with-syntax ([(E* ...) (reverse (syntax-e #'(E ...)))]
                    [(x  ...) temps]
                    [(x* ...) (reverse temps)])
        #'(let ([x* E*] ...)
            (F x ...))))]))

;; see that it works
(define (show x) (printf ">>> ~s\n" x) x)
(rev-app list (show 1) (show 2) (show 3))

Note that this is not shorter than the syntax-rules version, but it is easier to read since reverse and generate-temporaries have an obvious direct intention, eliminating the need to wonder through rewrite rules and inferring how they do their work. In addition, this macro expands in one step (use the macro stepper to compare it with the previous version), which makes it much more efficient.

Breaking Hygiene, How Bad is it?Tuesday, November 20th

We finally get to address the second deficiency of syntax-rules — its inability to intentionally capture an identifier so it is visible in user code. Let’s start with the simple version, the one that didn’t work:

(define-syntax-rule (if-it E1 E2 E3)
  (let ([it E1]) (if it E2 E3)))

and translate it to syntax-case:

(define-syntax (if-it stx)
  (syntax-case stx ()
    [(if-it E1 E2 E3)
    #'(let ([it E1]) (if it E2 E3))]))

The only problem here is that the it identifier is introduced by the macro, or more specifically, by the syntax form that makes up the return syntax. What we need now is a programmatic way to create an identifier with a lexical context that is different than the default. As mentioned above, Racket’s syntax system (and all other syntax-case systems) doesn’t provide a direct way to manipulate the lexical context. Instead, it provides a way to create a piece of syntax by copying the lexical scope of another one — and this is done with the datum->syntax function. The function consumes a syntax value to get the lexical scope from, and a “datum” which is an S-expression that can contain syntax values. The result will have these syntax values as given on the input, but raw S-expressions will be converted to syntaxes, using the given lexical context. In the above case, we need to convert an it symbol into the same-named identifier, and we can do that using the lexical scope of the input syntax. As we’ve seen before, we use with-syntax to inject the new identifier into the result:

(define-syntax (if-it stx)
  (syntax-case stx ()
    [(if-it E1 E2 E3)
    (with-syntax ([it (datum->syntax stx 'it)])
      #'(let ([it E1]) (if it E2 E3)))]))

We can even control the scope of the user binding — for example, it doesn’t make much sense to have it in the else branch. We can do this by first binding a plain (hygienic) identifier to the result, and only bind it to that when needed:

(define-syntax (if-it stx)
  (syntax-case stx ()
    [(if-it E1 E2 E3)
    (with-syntax ([it (datum->syntax stx 'it)])
      #'(let ([tmp E1]) (if tmp (let ([it tmp]) E2) E3)))]))

[A relevant note: Racket provides something that is known as “The Macro Writers Bill of Rights" --- in this case, it guarantees that the extralet` does not imply a runtime or a memory overhead.]

This works — and it’s a popular way for creating such user-visible bindings. However, breaking hygiene this way can lead to some confusing problems. Such problems are usually visible when we try to compose macros — for example, say that we want to create a cond-it macro, the anaphoric analogue of cond, which binds it in each branch. It seems that an obvious way of doing this is by layering it on top of if-it — it should even be simple enough to be defined with syntax-rules:

(define-syntax cond-it
  (syntax-rules (else)
    [(_ [test1 expr1 ...] [tests exprs ...] ...)
    (if-it test1
      (begin expr1 ...)
      (cond-it [tests exprs ...] ...))]
    ;; two end cases -- one with an `else' and one without
    [(_ [else expr ...]) (begin expr ...)]
    [(_) (void)]))

Surprisingly, this does not work! Can you see what went wrong?

The problem lies in how the it identifier is generated — it used the lexical context of the whole if-it expression, which seemed like exactly what we wanted. But in this case, the if-it expression is coming from the cond-it macro, not from the user input. Or to be more accurate: it’s the cond-it macro which is the user of if-it, so it is visible to cond-it, but not to its own users…

Note that these anaphoric macros are a popular example, but these problems do pop up elsewhere too. For example, imagine a loop macro that wants to bind break unhygienically, a class macro that binds this, and many others.

How can we solve this? There are several ways for this:

Macros in Racket’s Module SystemTuesday, November 20th

Not in PLAI

One of the main things that Racket pioneered is integrating its syntax system with its module system. In plain Racket (#lang racket, not the course languages), every file is a module that can provide some functionality, for when you put this code in a file:

#lang racket
(provide plus)
(define (plus x y) (+ x y))

You get a library that gives you a plus function. This is just the usual thing that you’d expect from a library facility in a language — but Racket allows you to do the same with syntax definitions. For example, if we add the following to this file:

(provide with)
(define-syntax-rule (with [x V] E)
  (let ([x V]) E))

we — the users of this library — also get to have a with binding, which is a “FLANG-compatibility” macro that expands into a let. Now, on a brief look, this doesn’t seem all too impressive, but conider the fact that with is actually a translation function that lives at the syntax level, as a kind of a compiler plugin, and you’ll see that this is not as trivial as it seems. Racket arranges to do this with a concept of instantiating code at the compiler level, so libraries are used in two ways: either the usual thing as a runtime instantiation, or at compile time.

Defining Languages in RacketTuesday, November 20th

But then Racket takes this concept even further. So far, we treated the thing that follows a #lang as a kind of a language specification — but the more complete story is that this specification is actually just a module. The only difference between such modules like racket or pl and “library modules” as our above file is that language modules provide a bunch of functionality that is specific to a language implementation. However, you don’t need to know about these things up front: instead, there’s a few tools that allow you to provide everything that some other module provides – if we add this to the above:

(provide (all-from-out racket))

then we get a library that provides the same two bindings as above (plus and with) — in addition to everything from the racket library (which it got from its own #lang racket line).

To use this file as a language, the last bit that we need to know about is the actual concrete level syntax. Racket provides an s-exp language which is a kind of a meta language for reading source code in the usual S-expression syntax. Assuming that the above is in a file called mylang.rkt, we can use it (from a different file in the same directory) as follows:

#lang s-exp "mylang.rkt"

which makes the language of this file be (a) read using the S-expression syntax, and (b) get its bindings from our module, so

#lang s-exp "mylang.rkt"
(with [x 10] (* x 4))

will show a result of 40.

So far this seems like just some awkward way to get to the same functionality as a simple library — but now we can use more tools to make things more interesting. First, we can provide everything from racket except for let — change the last provide to:

(provide (except-out (all-from-out racket) let))

Next, we can provide our with but make it have the name let instead — by replacing that (provide with) with:

(provide (rename-out [with let]))

The result is a language that is the same as Racket, except that it has an additional plus “built-in” function, and its let syntax is different, as specified by our macro:

#lang s-exp "mylang.rkt"
(let [x 10] (plus x 4))

To top things off, there are a few “special” implicit macros that Racket uses. One of them, #%app, is a macro that is used implicitly whenever there’s an expression that looks like a function application. In our terms, that’s the Call AST node that gets used whenever a braced-form isn’t one of the known forms. If we override this macro in a similar way that we did for let, we’re essentially changing the semantics of application syntax. For example, here’s a definition that makes it possible to use a @ keyword to get a list of results of applying a function on several arguments:

(define-syntax my-app
  (syntax-rules (@)
    [(_ F @ E ...)
    (list (F E) ...)]
    [(_ x ...) (x ...)]))

This makes the (my-app add1 @ 1 2) application evaluate to '(2 3), but if @ is not used (as the second subexpression), we get the usual function application. (Note that this is because the last clause expands to (x ...) which implicitly has the usual Racket function application.) We can now make our language replace Racket’s implicit #%app macro with this, in the same way as we did before: first, drop Racket’s version from what we provide:

(provide (except-out (all-from-out racket) let #%app))

and then provide our definition instead

(provide (rename-out [my-app #%app]))

Users of our language get this as the regular function application:

#lang s-exp "mylang.rkt"
(let [x (plus 6 10)] (sqrt @ (plus x -7) x (plus x 9)))

Since #%app is a macro, it can evaluate to anything, even to things that are not function applications at all. For example, here’s an extended definition that adds an arrow syntax that expands to a lambda expression not to an actual application:

(define-syntax my-app
  (syntax-rules (@ =>)
    [(_ F @ E ...)
    (list (F E) ...)]
    [(_ x => E ...)
    (lambda x E ...)]
    [(_ x ...) (x ...)]))

And an example of using it

#lang s-exp "mylang.rkt"
(define add1 ((x) => (+ x 1)))
;; or, combining all application forms in one example:
(((x) => (plus x 7)) @ 10 20 30)

Another such special macro is #%module-begin: this is a macro that is wrapped around the whole module body. Changing it makes it possible to change the semantics of a sequence of toplevel expressions in our language. The following is our complete language, with an example of redefining #%module-begin to create a “verbose” language that prints out expressions and what they evaluate to (note the verbose helper macro that is completely internal):

;; A language that is built as an extension on top of Racket

#lang racket

(provide (except-out (all-from-out racket)
                    let #%app #%module-begin))

(provide plus)
(define (plus x y) (+ x y))

(provide (rename-out [with let]))
(define-syntax-rule (with [x V] E)
                    (let ([x V]) E))

(provide (rename-out [my-app #%app]))
(define-syntax my-app
  (syntax-rules (=> @)
    [(_ x => E ...)
    (lambda x E ...)]
    [(_ F @ E ...)
    (list (F E) ...)]
    [(_ x ...) (x ...)]))

(provide (rename-out [mod-beg #%module-begin]))
(define-syntax-rule (mod-beg E ...)
                    (#%module-begin (verbose E) ...))
(define-syntax verbose
  (syntax-rules ()
    [(_ (define name value)) ; assume no (define (foo ...) ...)
    (begin (define name value)
            (printf "~s := ~s\n" 'name name))]
    [(_ E)
    (printf "~s --> ~s\n" 'E E)]))

And for reference, try that language with the above example:

#lang s-exp "mylang.rkt"
(define add1 ((x) => (+ x 1)))
(((x) => (plus x 7)) @ 10 20 30)

Macro ConclusionsTuesday, November 27th

PLAI §37.5

Macros are extremely powerful, but this also means that their usage should be restricted only to situations where they are really needed. You can view any function as extending the current collection of tools that you provide — where these tools are much more difficult for your users to swallow than plain functions: evaluation can happen in any way, with any scope, unlike the uniform rules of function application. An analogy is that every function (or value) that you provide is equivalent to adding nouns to a vocabulary, but macros can add completely new rules for reading, since using them might result in a completely different evaluation. Because of this, adding macros carelessly can make code harder to read and debug — and using them should be done in a way that is as clear as possible for users.

When should a macro be used?

It is also important to note that macros should not be used too frequently. As said above, every macro adds a completely different way of reading your code — a way that doesn’t use the usual “nouns” and “verbs”, but there are other reasons not to use a macro.

One common usage case is as an optimization — trying to avoid an extra function call. For example, this:

int min(int x, int y) {
  if ( x < y ) then return x; else return y;
}

might seem wasteful if you don’t want a full function call on every usage of min. So you might be tempted to use this instead:

#define min(x,y) x<y ? x : y

you even know the pitfalls of C macros so you make it more robust:

#define min(x,y) (((x)<(y)) ? (x) : (y))

But small functions like the above are things that any decent compiler should know how to optimize, and even if your compiler doesn’t, it’s still not worth doing this optimization because programmer time is the most expensive factor in any computer system. In addition, a compiler is committed to doing these optimizations only when possible (eg, it is not possible to in-line a recursive function) and to do proper in-lining — unlike the min CPP macro above which is erroneous in case x or y are expressions that have side-effects.

Side-note: macros in mainstream languagesTuesday, November 27th

Macros are an extremely powerful tool in Racket (and other languages in the Lisp family) — how come nobody else uses them?

Well, people have tried to use them in many contexts. The problem is that you cannot get away with a simple solution that does nothing more than textual manipulation of your programs. For example, the standard C preprocessor is a macro language, but it is fundamentally limited to very simple situations. This is still a hot topic these days, with modern languages trying out different solutions (or giving up and claiming that macros are evil).

Here is an example that was written by Mark Jason Dominus (“Higher Order Perl”), in a Perl mailing list post among further discussion on macros in Lisp vs other languages, including Perl’s source transformers that are supposed to fill a similar role.

The example starts with writing the following simple macro:

#define square(x) x*x

This doesn’t quite work because

2/square(10)

expands to

2/10*10

which is 2, but you wanted 0.02. So you need this instead:

#define square(x) (x*x)

but this breaks because

square(1+1)

expands to

(1+1*1+1)

which is 3, but you wanted 4. So you need this instead:

#define square(x) ((x)*(x))

But what about

x = 2;
square(x++)

which expands to

((x++)*(x++))

? So you need this instead:

int MYTMP;
#define square(x) (MYTMP = (x), MYTMP*MYTMP)

but now it only works for ints; you can’t do square(3.5) any more. To really fix this you have to use nonstandard extensions, something like:

#define square(x) ({typedef xtype = x; xtype xval = x; xval*xval; })

or more like:

#define square(x) \
  ({typedef xtype = (x); \
    xtype xval = (x); \
    xval*xval; })

And that’s just to get trivial macros, like “square()”, to work.


You should be able to appreciate now the tremendous power of macros. This is why there are so many “primitive features” of programming languages that can be considered as merely library functionality given a good macro system. For example, people are used to think about OOP as some inherent property of a language — but in Racket there are at least two very different object systems that it comes with, and several others in user-distributed code. All of these are implemented as a library which provides the functionality as well as the necessary syntax in the form of macros. So the basic principle is to have a small core language with powerful constructs, and make it easy to express complex ideas using these constructs.

This is an important point to consider before starting a new DSL (reminder: domain specific language) — if you need something that looks like a simple DSL but might grow to a full language, you can extend an existing language with macros to have the features you want, and you will always be able to grow to use the full language if necessary. This is particularly easy with Racket, but possible in other languages too.


Side note: the principle of a powerful but simple code language and easy extensions is not limited to using macros — other factors are involved, like first-class functions. In fact, “first class”-ness can help in many situations, for example: single inheritance + classes as first-class values can be used instead of multiple inheritance.

TypesTuesday, November 27th

PLAI §24

In our Toy language implementation, there are certain situations that are not covered. For example,

{< {+ 1 2} 3}

is not a problem, but

{+ {< 1 2} 3}

will eventually use Racket’s addition function on a boolean value, which will crash our evaluator. Assuming that we go back to the simple language we once had, where there were no booleans, we can still run into errors — except now these are the errors that our code raises:

{+ {fun {} 1} 2}

or

{1 2 3}

or

{{fun {x y} {+ x y}} 5}

In any case, it would be good to avoid such errors right from the start — it seems like we should be able to identify such bad code and not even try to run it. One thing that we can do is do a little more work at parse time, and declare the {1 2 3} program fragment as invalid. We can even try to forbid

{bind {{x 1}} {x 2 3}}

in the same way, but what should we do with this? —

{fun {x} {x 2 3}}

The validity of this depends on how it is used. The same goes for some invalid expressions — the above bogus expression can be fine if it’s in a context that shadows <:

{bind {{< *}}
  {+ {< 1 2} 3}}

Finally, consider this:

{+ 3 {if <mystery> 5 {fun {x} x}}}

where mystery contains something like random or read. In general, knowing whether a piece of code will run with no errors is a problem that is equivalent to the halting problem — and because of this, there is no way to create an “exact” type system: they are all either too restrictive (rejecting programs that would run with no errors) or too permissive (accepting programs that might crash). This is a very practical issue — type safety means a lot less bugs in the system. A good type system is still an actively researched problem.

What is a Type?Tuesday, November 27th

PLAI §25

A type is any property of a program (or an expression) that can be determined without running the program. (This is different than what is considered a type in Racket which is a property that is known only at run-time, which means that before run-time we know nothing so in essence we have a single type (in the static sense).) Specifically, we want to use types in a way that predicts some aspects of the program’s behavior, for example, whether a program will crash.

Usually, types are being used as the kind of value that an expression can evaluate to, not the precise value itself. For example, we might have two kinds of values — functions and numbers, and we know that addition always operates on numbers, therefore

{+ 1 {fun {x} x}}

is a type error. Note that to determine this we don’t care about the actual function, just the fact that it is a function.

Important: types can discriminate certain programs as invalid, but they cannot discriminate correct programs from incorrect ones. For example, there is no way for any type system to know that this:

{fun {x} {+ x 1}}

is an incorrect decrease-by-one function.

In general, type systems try to get to the optimal point where as much information as possible is known, yet the language is not too restricted, no significant computing resources are wasted, and programmers don’t spend much time annotating their code.

Why would you want to use a type system?

Our Types — The Picky LanguageTuesday, November 27th

The first thing we need to do is to agree on what types are. Earlier, we talked about two types: numbers and functions (ignore booleans or anything else for now), we will use these two types for now.

In general, this means that we are using the Types are Sets meaning for types, and specifically, we will be implmenting a type system known as a Hindley-Milner system. This is not what Typed Racket is using. In fact, one of the main differences is that in our type system each binding has exactly one type, whereas in Typed Racket an identifier can have different types in different places in the code. An example of this is something that we’ve talked about earlier:

(: foo : (U String Number) -> Number)
(define (foo x)          ;\ these `x`s have a
  (if (number? x)        ;/ (U Number String) type
    (+ x 1)              ;> this one is a Number
    (string-length x)))  ;> and this one is a String

A type system is presented as a collection of rules called “type judgments”, which describe how to determine the type of an expression. Beside the types and the judgments, a type system specification needs a (decidable) algorithm that can assign types to expressions.

Such a specification should have one rule for every kind of syntactic construct, so when we get a program we can determine the precise type of any expression. Also, these judgments are usually recursive since a type judgment will almost always rely on the types of sub-expressions (if any).

For our restricted system, we have two rules (= judgments) that we can easily specify:

n : Number  (any numeral `n' is a number)
{fun {x} E} : Function

And what about an identifier? Well, it is clear that we need to keep some form of an environment that will keep an account of types assigned to identifiers (note: all of this is not at run-time). This environment is used in all type judgments, and usually written as a capital Greek Gamma character (in some places G is used to stick to ASCII texts). The conventional way to write the two rules above is:

Γ ⊢ n : Number
Γ ⊢ {fun {x} E} : Function

The first one is read as “Gamma proves that n has the type Number”. Note that this is a syntactic environment, much like DE-ENVs that you have seen in homework.

So, we can write a rule for identifiers that simply has the type assigned by the environment:

Γ ⊢ x : Γ(x)

We now need a rule for addition and a rule for application (note: we’re using a very limited subset of our old language, where arithmetic operators are not function applications). Addition is easy: if we can prove that both a and b are numbers in some environment Γ, then we know that {+ a b} is a number in the same environment. We write this as follows:

Γ ⊢ A : Number  Γ ⊢ B : Number
———————————————————————————————
    Γ ⊢ {+ A B} : Number

Now, what about application? We need to refer to some arbitrary type now, and the common letter for that is a Greek lowercase tau:

Γ ⊢ F : Function  Γ ⊢ V : τₐ
—————————————————————————————
    Γ ⊢ {call F V} : ???

that is — if we can prove that f is a function, and that v is a value of some type τₐ, then … ??? Well, we need to know more about f: we need to know what type it consumes and what type it returns. So a simple function is not enough — we need some sort of a function type that specifies both input and output types. We will use the notation that was seen throughout the semester and dump function. Now we can write:

Γ ⊢ F : (τ₁ -> τ₂)  Γ ⊢ V : τ₁
——————————————————————————————
    Γ ⊢ {call F V} : τ₂

which makes sense — if you take a function of type τ₁->τ₂ and you feed it what it expects, you get the obvious output type. But going back to the language — where do we get these new arrow types from? We will modify the language and require that every function specifies its input and output type (and assume we have only one argument functions). For example, we will write something like this for a function that is the curried version of addition:

{fun {x : Number} : (Number -> Number)
  {fun {y : Number} : Number
    {+ x y}}}

So: the revised syntax for the limited language that contains only additions, applications and single-argument functions, and for fun — go back to using the call keyword is. The syntax we get is:

<PICKY> ::= <num>
          | <id>
          | { + <PICKY> <PICKY> }
          | { fun { <id> : <TYPE> } : <TYPE> <PICKY> }
          | { call <PICKY> <PICKY> }

<TYPE>  ::= Number
          | ( <TYPE> -> <TYPE> )

and the typing rules are:

Γ ⊢ n : Number

Γ ⊢ {fun {x : τ₁} : τ₂ E} : (τ₁ -> τ₂)

Γ ⊢ x : Γ(x)

Γ ⊢ A : Number  Γ ⊢ B : Number
———————————————————————————————
    Γ ⊢ {+ A B} : Number

Γ ⊢ F : (τ₁ -> τ₂)  Γ ⊢ V : τ₁
——————————————————————————————
    Γ ⊢ {call F V} : τ₂

But we’re still missing a big part — the current rule for a fun expression is too weak, it does not allow us to conclude that this expression:

{fun {x : Number} : (Number -> Number)
  3}

is invalid. Instead, it will make us think that this program:

{call {call {fun {x : Number} : (Number -> Number)
              3}
            5}
      7}

is valid, and should return a number. What’s missing? We need to check that the body part of the function is correct, so the rule for typing a fun is no longer a simple one. Here is how we check the body instead of blindly believing program annotations:

          Γ[x:=τ₁] ⊢ E : τ₂
——————————————————————————————————————
Γ ⊢ {fun {x : τ₁} : τ₂ E} : (τ₁ -> τ₂)

That is — we want to make sure that if x has type τ₁, then the body expression E has type τ₂, and if we can prove this, then we can trust these annotations.

There is an important relationship between this rule and the call rule for application:

(Side note: Racket comes with a contract system that can identify type errors dynamically, and assign blame to either the caller or the callee — and these correspond to these two sides.)

Note that, as we said, number is really just a property of a certain kind of values, we don’t know exactly what numbers are actually used. In the same way, the arrow function types don’t tell us exactly what function it is, for example, (Number -> Number) can indicate a function that adds three to its argument, subtracts seven, or multiplies it by 7619. But it certainly contains much more than the previous naive function type. (Consider also Typed Racket here: it goes much further in expressing facts about code.)

For reference, here is the complete BNF and typing rules:

<PICKY> ::= <num>
          | <id>
          | { + <PICKY> <PICKY> }
          | { fun { <id> : <TYPE> } : <TYPE> <PICKY> }
          | { call <PICKY> <PICKY> }

<TYPE>  ::= Number
          | ( <TYPE> -> <TYPE> )

Γ ⊢ n : Number

Γ ⊢ x : Γ(x)

Γ ⊢ A : Number  Γ ⊢ B : Number
———————————————————————————————
    Γ ⊢ {+ A B} : Number

          Γ[x:=τ₁] ⊢ E : τ₂
——————————————————————————————————————
Γ ⊢ {fun {x : τ₁} : τ₂ E} : (τ₁ -> τ₂)

Γ ⊢ F : (τ₁ -> τ₂)  Γ ⊢ V : τ₁
——————————————————————————————
    Γ ⊢ {call F V} : τ₂

Examples of using types (abbreviate Number as Num) — first, a simple example:

                {} ⊢ 5 : Num  {} ⊢ 7 : Num
                ———————————————————————————
{} ⊢ 2 : Num        {} ⊢ {+ 5 7} : Num
—————————————————————————————————————————————
          {} ⊢ {+ 2 {+ 5 7}} : Num

and a little more involved one:

    [x:=Num] ⊢ x : Num  [x:=Num] ⊢ 3 : Num
    ———————————————————————————————————————
          [x:=Num] ⊢ {+ x 3} : Num
———————————————————————————————————————————————
{} ⊢ {fun {x : Num} : Num {+ x 3}} : Num -> Num  {} ⊢ 5 : Num
——————————————————————————————————————————————————————————————
      {} ⊢ {call {fun {x : Num} : Num {+ x 3}} 5} : Num

Finally, try a buggy program like

{+ 3 {fun {x : Number} : Number x}}

and see where it is impossible to continue.

The main thing here is that to know that this is a type error, we have to prove that there is no judgment for a certain type (in this case, no way to prove that a fun expression has a Num type), which we (humans) can only do by inspecting all of the rules. Because of this, we need to also add an algorithm to our type system, one that we can follow and determine when it gives up.

Typing controlTuesday, November 27th

PLAI §26

We will now extend our typed Picky language to have a conditional expression, and predicates. First, we extend the BNF with a predicate expression, and we also need a type for the results:

<PICKY> ::= <num>
          | <id>
          | { + <PICKY> <PICKY> }
          | { < <PICKY> <PICKY> }
          | { fun { <id> : <TYPE> } : <TYPE> <PICKY> }
          | { call <PICKY> <PICKY> }
          | { if <PICKY> <PICKY> <PICKY> }

<TYPE>  ::= Number
          | Boolean
          | ( <TYPE> -> <TYPE> )

Initially, we use the same rules, and add the obvious type for the predicate:

Γ ⊢ A : Number  Γ ⊢ B : Number
———————————————————————————————
    Γ ⊢ {< A B} : Boolean

And what should the rule for if look like? Well, to make sure that the condition is a boolean, it should be something of this form:

Γ ⊢ C : Boolean  Γ ⊢ T : ???  Γ ⊢ E : ???
———————————————————————————————————————————
          Γ ⊢ {if C T E} : ???

What would be the types of t and e? A natural choice would be to let the programmer use any two types:

Γ ⊢ C : Boolean  Γ ⊢ T : τ₁  Γ ⊢ E : τ₂
—————————————————————————————————————————
          Γ ⊢ {if C T E} : ???

But what would the return type be? This is still a problem. (BTW, some kind of a union would be nice, but it has some strong implications that we will not discuss.) In addition, we will have a problem detecting possible errors like:

{+ 2 {if <mystery> 3 {fun {x} x}}}

Since we know nothing about the condition, we can just as well be conservative and force both arms to have the same type. The rule is therefore:

Γ ⊢ C : Boolean  Γ ⊢ T : τ  Γ ⊢ E : τ
———————————————————————————————————————
          Γ ⊢ {if C T E} : τ

— using the same letter indicates that we expect the types to be identical, unlike the previous attempt. Consequentially, this type system is fundamentally weaker than Typed Racket which we use in this class.

Here is the complete language specification with this extension:

<PICKY> ::= <num>
          | <id>
          | { + <PICKY> <PICKY> }
          | { < <PICKY> <PICKY> }
          | { fun { <id> : <TYPE> } : <TYPE> <PICKY> }
          | { call <PICKY> <PICKY> }
          | { if <PICKY> <PICKY> <PICKY> }

<TYPE>  ::= Number
          | Boolean
          | ( <TYPE> -> <TYPE> )

Γ ⊢ n : Number

Γ ⊢ x : Γ(x)

Γ ⊢ A : Number  Γ ⊢ B : Number
———————————————————————————————
    Γ ⊢ {+ A B} : Number

Γ ⊢ A : Number  Γ ⊢ B : Number
———————————————————————————————
    Γ ⊢ {< A B} : Boolean

          Γ[x:=τ₁] ⊢ E : τ₂
——————————————————————————————————————
Γ ⊢ {fun {x : τ₁} : τ₂ E} : (τ₁ -> τ₂)

Γ ⊢ F : (τ₁ -> τ₂)  Γ ⊢ V : τ₁
——————————————————————————————
    Γ ⊢ {call F V} : τ₂

Γ ⊢ C : Boolean  Γ ⊢ T : τ  Γ ⊢ E : τ
———————————————————————————————————————
          Γ ⊢ {if C T E} : τ

Extending PickyTuesday, November 27th

In general, we can extend this language in one of two ways. For example, lets say that we want to add the with form. One way to add it is what we did above — simply add it to the language, and write the rule for it. In this case, we get:

Γ ⊢ V : τ₁  Γ[x:=τ₁] ⊢ E : τ₂
——————————————————————————————
Γ ⊢ {with {x : τ₁ V} E} : τ₂

Note how this rule encapsulates information about the scope of with. Also note that we need to specify the types for the bound values.

Another way to achieve this extension is if we add with as a derived rule. We know that when we see a

{with {x V} E}

expression, we can just translate it into

{call {fun {x} E} V}

So we could achieve this extension by using a rewrite rule to translate all with expressions into calls of anonymous functions (eg, using the with-stx facility that we have seen recently). This could be done formally: begin with the with form, translate to the call form, and finally show the necessary goals to prove its type. The only thing to be aware of is the need to translate the types too, and there is one type that is missing from the typed-with version above — the output type of the function. This is an indication that we don’t really need to specify function output types — we can just deduce them from the code, provided that we know the input type to the function.

Indeed, if we do this on a general template for a with expression, then we end up with the same goals that need to be proved as in the above rule:

      Γ[x:=τ₁] ⊢ E : τ₂
——————————————————————————————————————
Γ ⊢ {fun {x : τ₁} : τ₂ E} : (τ₁ -> τ₂)      Γ ⊢ V : τ₁
———————————————————————————————————————————————————————
        Γ ⊢ {call {fun {x : τ₁} : τ₂ E} V} : τ₂
        ———————————————————————————————————————
            Γ ⊢ {with {x : τ₁ V} E} : τ₂

Conclusion — we’ve seen type judgment rules, and using them in proof trees. Note that in these trees there is a clear difference between rules that have no preconditions — there are axioms that are always true (eg, a numeral is always of type num).

The general way of proving a type seems similar to evaluation of an expression, but there is a huge difference — nothing is really getting evaluated. As an example, we always go into the body of a function expression, which is done to get the function’s type, and this is later used anywhere this function is used — when you evaluate this:

{with {f {fun {x : Number} : Number x}}
  {+ {call f 1} {call f 2}}}

you first create a closure which means that you don’t touch the body of the function, and later you use it twice. In contrast, when you prove the type of this expression, you immediately go into the body of the function which you have to do to prove that it has the expected Number->Number type, and then you just use this type twice.

Finally, we have seen the importance of using the same type letters to enforce types, and in the case of typing an if statement this had a major role: specifying that the two arms can be any two types, or the same type.

Implementing PickyTuesday, November 27th

The following is a simple implementation of the Picky language. It is based on the environments-based Flang implementation. Note the two main functions here — typecheck and typecheck*.

;;; ---<<<PICKY1>>>-------------------------------------------------
;; The Picky interpreter, verbose version

#lang pl

#|
The grammar:
  <PICKY> ::= <num>
            | <id>
            | { + <PICKY> <PICKY> }
            | { - <PICKY> <PICKY> }
            | { = <PICKY> <PICKY> }
            | { < <PICKY> <PICKY> }
            | { fun { <id> : <TYPE> } : <TYPE> <PICKY> }
            | { call <PICKY> <PICKY> }
            | { with { <id> : <TYPE> <PICKY> } <PICKY> }
            | { if <PICKY> <PICKY> <PICKY> }
  <TYPE>  ::= Num | Number
            | Bool | Boolean
            | { <TYPE> -> <TYPE> }

Evaluation rules:
  eval(N,env)                = N
  eval(x,env)                = lookup(x,env)
  eval({+ E1 E2},env)        = eval(E1,env) + eval(E2,env)
  eval({- E1 E2},env)        = eval(E1,env) - eval(E2,env)
  eval({= E1 E2},env)        = eval(E1,env) = eval(E2,env)
  eval({< E1 E2},env)        = eval(E1,env) < eval(E2,env)
  eval({fun {x} E},env)      = <{fun {x} E}, env>
  eval({call E1 E2},env1)
          = eval(Ef,extend(x,eval(E2,env1),env2))
                            if eval(E1,env1) = <{fun {x} Ef}, env2>
          = error!          otherwise -- but this doesn't happen
  eval({with {x E1} E2},env) = eval(E2,extend(x,eval(E1,env),env))
  eval({if E1 E2 E3},env)    = eval(E2,env)  if eval(E1,env) is true
                            = eval(E3,env)  otherwise

Type checking rules:

  Γ ⊢ n : Number

  Γ ⊢ x : Γ(x)

  Γ ⊢ A : Number  Γ ⊢ B : Number
  ———————————————————————————————
      Γ ⊢ {+ A B} : Number

  Γ ⊢ A : Number  Γ ⊢ B : Number
  ———————————————————————————————
      Γ ⊢ {< A B} : Boolean

            Γ[x:=τ₁] ⊢ E : τ₂
  ——————————————————————————————————————
  Γ ⊢ {fun {x : τ₁} : τ₂ E} : (τ₁ -> τ₂)

  Γ ⊢ F : (τ₁ -> τ₂)  Γ ⊢ V : τ₁
  ——————————————————————————————
      Γ ⊢ {call F V} : τ₂

  Γ ⊢ V : τ₁  Γ[x:=τ₁] ⊢ E : τ₂
  ——————————————————————————————
  Γ ⊢ {with {x : τ₁ V} E} : τ₂

  Γ ⊢ C : Boolean  Γ ⊢ T : τ  Γ ⊢ E : τ
  ———————————————————————————————————————
            Γ ⊢ {if C T E} : τ

|#

(define-type PICKY
  [Num  Number]
  [Id    Symbol]
  [Add  PICKY PICKY]
  [Sub  PICKY PICKY]
  [Equal PICKY PICKY]
  [Less  PICKY PICKY]
  [Fun  Symbol TYPE PICKY TYPE] ; name, in-type, body, out-type
  [Call  PICKY PICKY]
  [With  Symbol TYPE PICKY PICKY]
  [If    PICKY PICKY PICKY])

(define-type TYPE
  [NumT]
  [BoolT]
  [FunT TYPE TYPE])

(: parse-sexpr : Sexpr -> PICKY)
;; parses s-expressions into PICKYs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(list '+ lhs rhs) (Add  (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '- lhs rhs) (Sub  (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '= lhs rhs) (Equal (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '< lhs rhs) (Less  (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list 'call fun arg)
                      (Call  (parse-sexpr fun) (parse-sexpr arg))]
    [(list 'if c t e)
    (If (parse-sexpr c) (parse-sexpr t) (parse-sexpr e))]
    [(cons 'fun more)
    (match sexpr
      [(list 'fun (list (symbol: name) ': itype) ': otype body)
        (Fun name
            (parse-type-sexpr itype)
            (parse-sexpr body)
            (parse-type-sexpr otype))]
      [else (error 'parse-sexpr "bad `fun' syntax in ~s" sexpr)])]
    [(cons 'with more)
    (match sexpr
      [(list 'with (list (symbol: name) ': type named) body)
        (With name
              (parse-type-sexpr type)
              (parse-sexpr named)
              (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `with' syntax in ~s" sexpr)])]
    [else (error 'parse-sexpr "bad expression syntax: ~s" sexpr)]))

(: parse-type-sexpr : Sexpr -> TYPE)
;; parses s-expressions into TYPEs
(define (parse-type-sexpr sexpr)
  (match sexpr
    ['Number  (NumT)]
    ['Boolean (BoolT)]
    ;; allow shorter names too
    ['Num  (NumT)]
    ['Bool (BoolT)]
    [(list itype '-> otype)
    (FunT (parse-type-sexpr itype) (parse-type-sexpr otype))]
    [else (error 'parse-type-sexpr "bad type syntax in ~s" sexpr)]))

(: parse : String -> PICKY)
;; parses a string containing a PICKY expression to a PICKY AST
(define (parse str)
  (parse-sexpr (string->sexpr str)))

;; Typechecker and related types and helpers

;; this is similar to ENV, but it holds type information for the
;; identifiers during typechecking
(define-type TYPEENV
  [EmptyTypeEnv]
  [ExtendTypeEnv Symbol TYPE TYPEENV])

(: type-lookup : Symbol TYPEENV -> TYPE)
;; similar to `lookup' for type environments; note that the
;; error is phrased as a typecheck error, since this indicates
;; a failure at the type checking stage
(define (type-lookup name typeenv)
  (cases typeenv
    [(EmptyTypeEnv) (error 'typecheck "no binding for ~s" name)]
    [(ExtendTypeEnv id type rest-env)
    (if (eq? id name) type (type-lookup name rest-env))]))

(: typecheck : PICKY TYPE TYPEENV -> Void)
;; Checks that the given expression has the specified type.
;; Used only for side-effects (to throw a type error), so return
;; a void value.
(define (typecheck expr type type-env)
  (unless (equal? type (typecheck* expr type-env))
    (error 'typecheck "type error for ~s: expecting a ~s"
          expr type)))

(: typecheck* : PICKY TYPEENV -> TYPE)
;; Returns the type of the given expression (which also means
;; that it checks it).  This is a helper for the real typechecker
;; that also checks a specific return type.
(define (typecheck* expr type-env)
  (: two-nums : PICKY PICKY -> Void)
  (define (two-nums e1 e2)
    (typecheck e1 (NumT) type-env)
    (typecheck e2 (NumT) type-env))
  (cases expr
    [(Num n) (NumT)]
    [(Id name) (type-lookup name type-env)]
    [(Add  l r) (two-nums l r) (NumT)]
    [(Sub  l r) (two-nums l r) (NumT)]
    [(Equal l r) (two-nums l r) (BoolT)]
    [(Less  l r) (two-nums l r) (BoolT)]
    [(Fun bound-id in-type bound-body out-type)
    (typecheck bound-body out-type
                (ExtendTypeEnv bound-id in-type type-env))
    (FunT in-type out-type)]
    [(Call fun arg)
    (cases (typecheck* fun type-env)
      [(FunT in-type out-type)
        (typecheck arg in-type type-env)
        out-type]
      [else (error 'typecheck "type error for ~s: expecting a fun"
                    expr)])]
    [(With bound-id itype named-expr bound-body)
    (typecheck named-expr itype type-env)
    (typecheck* bound-body
                (ExtendTypeEnv bound-id itype type-env))]
    [(If cond-expr then-expr else-expr)
    (typecheck cond-expr (BoolT) type-env)
    (let ([type (typecheck* then-expr type-env)])
      (typecheck else-expr type type-env) ; enforce same type
      type)]))

;; Evaluator and related types and helpers

(define-type ENV
  [EmptyEnv]
  [Extend Symbol VAL ENV])

(define-type VAL
  [NumV  Number]
  [BoolV Boolean]
  [FunV  Symbol PICKY ENV])

(: lookup : Symbol ENV -> VAL)
;; lookup a symbol in an environment, return its value or throw an
;; error if it isn't bound
(define (lookup name env)
  (cases env
    [(EmptyEnv) (error 'lookup "no binding for ~s" name)]
    [(Extend id val rest-env)
    (if (eq? id name) val (lookup name rest-env))]))

(: strip-numv : Symbol VAL -> Number)
;; converts a VAL to a Racket number if possible, throws an error if
;; not using the given name for the error message
(define (strip-numv name val)
  (cases val
    [(NumV n) n]
    ;; this error will never be reached, see below for more
    [else (error name "expected a number, got: ~s" val)]))

(: arith-op : (Number Number -> Number) VAL VAL -> VAL)
;; gets a Racket numeric binary operator, and uses it within a NumV
;; wrapper
(define (arith-op op val1 val2)
  (NumV (op (strip-numv 'arith-op val1)
            (strip-numv 'arith-op val2))))

(: bool-op : (Number Number -> Boolean) VAL VAL -> VAL)
;; gets a Racket numeric binary predicate, and uses it
;; within a BoolV wrapper
(define (bool-op op val1 val2)
  (BoolV (op (strip-numv 'bool-op val1)
            (strip-numv 'bool-op val2))))

(: eval : PICKY ENV -> VAL)
;; evaluates PICKY expressions by reducing them to values
(define (eval expr env)
  (cases expr
    [(Num n) (NumV n)]
    [(Id name) (lookup name env)]
    [(Add  l r) (arith-op + (eval l env) (eval r env))]
    [(Sub  l r) (arith-op - (eval l env) (eval r env))]
    [(Equal l r) (bool-op  = (eval l env) (eval r env))]
    [(Less  l r) (bool-op  < (eval l env) (eval r env))]
    [(Fun bound-id in-type bound-body out-type)
    ;; note that types are not used at runtime,
    ;; so they're not stored in the closure
    (FunV bound-id bound-body env)]
    [(Call fun-expr arg-expr)
    (let ([fval (eval fun-expr env)])
      (cases fval
        [(FunV bound-id bound-body f-env)
          (eval bound-body
                (Extend bound-id (eval arg-expr env) f-env))]
        ;; `cases' requires complete coverage of all variants, but
        ;; this `else' is never used since we typecheck programs
        [else (error 'eval "`call' expects a function, got: ~s"
                            fval)]))]
    [(With bound-id type named-expr bound-body)
    (eval bound-body (Extend bound-id (eval named-expr env) env))]
    [(If cond-expr then-expr else-expr)
    (let ([bval (eval cond-expr env)])
      (if (cases bval
            [(BoolV b) b]
            ;; same as above: this case is never reached
            [else (error 'eval "`if' expects a boolean, got: ~s"
                                bval)])
        (eval then-expr env)
        (eval else-expr env)))]))

(: run : String -> Number)
;; evaluate a PICKY program contained in a string
(define (run str)
  (let ([prog (parse str)])
    (typecheck prog (NumT) (EmptyTypeEnv))
    (let ([result (eval prog (EmptyEnv))])
      (cases result
        [(NumV n) n]
        ;; this error is never reached, since we make sure
        ;; that the program always evaluates to a number above
        [else (error 'run "evaluation returned a non-number: ~s"
                          result)]))))

;; tests -- including translations of the FLANG tests
(test (run "5") => 5)
(test (run "{< 1 2}") =error> "type error")
(test (run "{fun {x : Num} : Num {+ x 1}}") =error> "type error")
(test (run "{call {fun {x : Num} : Num {+ x 1}} 4}") => 5)
(test (run "{with {x : Num 3} {+ x 1}}") => 4)
(test (run "{with {identity : {Num -> Num} {fun {x : Num} : Num x}}
              {call identity 1}}")
      => 1)
(test (run "{with {add3 : {Num -> Num}
                  {fun {x : Num} : Num {+ x 3}}}
              {call add3 1}}")
      => 4)
(test (run "{with {add3 : {Num -> Num}
                  {fun {x : Num} : Num {+ x 3}}}
              {with {add1 : {Num -> Num}
                    {fun {x : Num} : Num {+ x 1}}}
                {with {x : Num 3}
                  {call add1 {call add3 x}}}}}")
      => 7)
(test (run "{with {identity : {{Num -> Num} -> {Num -> Num}}
                  {fun {x : {Num -> Num}} : {Num -> Num} x}}
              {with {foo : {Num -> Num}
                    {fun {x : Num} : Num {+ x 1}}}
                {call {call identity foo} 123}}}")
      => 124)
(test (run "{with {x : Num 3}
              {with {f : {Num -> Num}
                    {fun {y : Num} : Num {+ x y}}}
                {with {x : Num 5}
                  {call f 4}}}}")
      => 7)
(test (run "{call {with {x : Num 3}
                    {fun {y : Num} : Num {+ x y}}}
                  4}")
      => 7)
(test (run "{with {f : {Num -> Num}
                  {with {x : Num 3} {fun {y : Num} : Num {+ x y}}}}
              {with {x : Num 100}
                {call f 4}}}")
      => 7)
(test (run "{call {call {fun {x : {Num -> {Num -> Num}}}
                            : {Num -> Num}
                          {call x 1}}
                        {fun {x : Num} : {Num -> Num}
                          {fun {y : Num} : Num {+ x y}}}}
                  123}")
      => 124)
(test (run "{call {fun {x : Num} : Num {if {< x 2} {+ x 5} {+ x 6}}}
                  1}")
      => 6)
(test (run "{call {fun {x : Num} : Num {if {< x 2} {+ x 5} {+ x 6}}}
                  2}")
      => 8)

One thing that is very obvious when you look at the examples is that this language is way too verbose to be practical — types are repeated over and over again. If you look carefully at the typechecking fragments for the two relevant expressions — fun and with — you can see that we can actually get rid of almost all of the type annotations. The following version does that, there are no types mentioned except for the input type for a function. Note that we can do that at this point because our language is so simple that many pieces of code have a specific type. (For example, if we add polymorphism things get more complicated.)

;;; ---<<<PICKY2>>>-------------------------------------------------
;; The Picky interpreter, almost no explicit types

#lang pl

#|
The grammar:
  <PICKY> ::= <num>
            | <id>
            | { + <PICKY> <PICKY> }
            | { - <PICKY> <PICKY> }
            | { = <PICKY> <PICKY> }
            | { < <PICKY> <PICKY> }
            | { fun { <id> : <TYPE> } <PICKY> }
            | { call <PICKY> <PICKY> }
            | { with { <id> <PICKY> } <PICKY> }
            | { if <PICKY> <PICKY> <PICKY> }
  <TYPE>  ::= Num | Number
            | Bool | Boolean
            | { <TYPE> -> <TYPE> }

Evaluation rules:
  eval(N,env)                = N
  eval(x,env)                = lookup(x,env)
  eval({+ E1 E2},env)        = eval(E1,env) + eval(E2,env)
  eval({- E1 E2},env)        = eval(E1,env) - eval(E2,env)
  eval({= E1 E2},env)        = eval(E1,env) = eval(E2,env)
  eval({< E1 E2},env)        = eval(E1,env) < eval(E2,env)
  eval({fun {x} E},env)      = <{fun {x} E}, env>
  eval({call E1 E2},env1)
          = eval(Ef,extend(x,eval(E2,env1),env2))
                            if eval(E1,env1) = <{fun {x} Ef}, env2>
          = error!          otherwise -- but this doesn't happen
  eval({with {x E1} E2},env) = eval(E2,extend(x,eval(E1,env),env))
  eval({if E1 E2 E3},env)    = eval(E2,env)  if eval(E1,env) is true
                            = eval(E3,env)  otherwise

Type checking rules (note how implicit types are made):

  Γ ⊢ n : Number

  Γ ⊢ x : Γ(x)

  Γ ⊢ A : Number  Γ ⊢ B : Number
  ———————————————————————————————
      Γ ⊢ {+ A B} : Number

  Γ ⊢ A : Number  Γ ⊢ B : Number
  ———————————————————————————————
      Γ ⊢ {< A B} : Boolean

          Γ[x:=τ₁] ⊢ E : τ₂
  —————————————————————————————————
  Γ ⊢ {fun {x : τ₁} E} : (τ₁ -> τ₂)

  Γ ⊢ F : (τ₁ -> τ₂)  Γ ⊢ V : τ₁
  ——————————————————————————————
      Γ ⊢ {call F V} : τ₂

  Γ ⊢ V : τ₁  Γ[x:=τ₁] ⊢ E : τ₂
  ——————————————————————————————
    Γ ⊢ {with {x V} E} : τ₂

  Γ ⊢ C : Boolean  Γ ⊢ T : τ  Γ ⊢ E : τ
  ———————————————————————————————————————
            Γ ⊢ {if C T E} : τ

|#

(define-type PICKY
  [Num  Number]
  [Id    Symbol]
  [Add  PICKY PICKY]
  [Sub  PICKY PICKY]
  [Equal PICKY PICKY]
  [Less  PICKY PICKY]
  [Fun  Symbol TYPE PICKY]  ; no output type
  [Call  PICKY PICKY]
  [With  Symbol PICKY PICKY] ; no types here
  [If    PICKY PICKY PICKY])

(define-type TYPE
  [NumT]
  [BoolT]
  [FunT TYPE TYPE])

(: parse-sexpr : Sexpr -> PICKY)
;; parses s-expressions into PICKYs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(list '+ lhs rhs) (Add  (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '- lhs rhs) (Sub  (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '= lhs rhs) (Equal (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '< lhs rhs) (Less  (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list 'call fun arg)
                      (Call  (parse-sexpr fun) (parse-sexpr arg))]
    [(list 'if c t e)
    (If (parse-sexpr c) (parse-sexpr t) (parse-sexpr e))]
    [(cons 'fun more)
    (match sexpr
      [(list 'fun (list (symbol: name) ': itype) body)
        (Fun name (parse-type-sexpr itype) (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `fun' syntax in ~s" sexpr)])]
    [(cons 'with more)
    (match sexpr
      [(list 'with (list (symbol: name) named) body)
        (With name (parse-sexpr named) (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `with' syntax in ~s" sexpr)])]
    [else (error 'parse-sexpr "bad expression syntax: ~s" sexpr)]))

(: parse-type-sexpr : Sexpr -> TYPE)
;; parses s-expressions into TYPEs
(define (parse-type-sexpr sexpr)
  (match sexpr
    ['Number  (NumT)]
    ['Boolean (BoolT)]
    ;; allow shorter names too
    ['Num  (NumT)]
    ['Bool (BoolT)]
    [(list itype '-> otype)
    (FunT (parse-type-sexpr itype) (parse-type-sexpr otype))]
    [else (error 'parse-type-sexpr "bad type syntax in ~s" sexpr)]))

(: parse : String -> PICKY)
;; parses a string containing a PICKY expression to a PICKY AST
(define (parse str)
  (parse-sexpr (string->sexpr str)))

;; Typechecker and related types and helpers

;; this is similar to ENV, but it holds type information for the
;; identifiers during typechecking
(define-type TYPEENV
  [EmptyTypeEnv]
  [ExtendTypeEnv Symbol TYPE TYPEENV])

(: type-lookup : Symbol TYPEENV -> TYPE)
;; similar to `lookup' for type environments; note that the
;; error is phrased as a typecheck error, since this indicates
;; a failure at the type checking stage
(define (type-lookup name typeenv)
  (cases typeenv
    [(EmptyTypeEnv) (error 'typecheck "no binding for ~s" name)]
    [(ExtendTypeEnv id type rest-env)
    (if (eq? id name) type (type-lookup name rest-env))]))

(: typecheck : PICKY TYPE TYPEENV -> Void)
;; Checks that the given expression has the specified type.
;; Used only for side-effects (to throw a type error), so return
;; a void value.
(define (typecheck expr type type-env)
  (unless (equal? type (typecheck* expr type-env))
    (error 'typecheck "type error for ~s: expecting a ~s"
          expr type)))

(: typecheck* : PICKY TYPEENV -> TYPE)
;; Returns the type of the given expression (which also means
;; that it checks it).  This is a helper for the real typechecker
;; that also checks a specific return type.
(define (typecheck* expr type-env)
  (: two-nums : PICKY PICKY -> Void)
  (define (two-nums e1 e2)
    (typecheck e1 (NumT) type-env)
    (typecheck e2 (NumT) type-env))
  (cases expr
    [(Num n) (NumT)]
    [(Id name) (type-lookup name type-env)]
    [(Add  l r) (two-nums l r) (NumT)]
    [(Sub  l r) (two-nums l r) (NumT)]
    [(Equal l r) (two-nums l r) (BoolT)]
    [(Less  l r) (two-nums l r) (BoolT)]
    [(Fun bound-id in-type bound-body)
    (FunT in-type
          (typecheck* bound-body
                      (ExtendTypeEnv bound-id in-type type-env)))]
    [(Call fun arg)
    (cases (typecheck* fun type-env)
      [(FunT in-type out-type)
        (typecheck arg in-type type-env)
        out-type]
      [else (error 'typecheck "type error for ~s: expecting a fun"
                    expr)])]
    [(With bound-id named-expr bound-body)
    (typecheck* bound-body
                (ExtendTypeEnv bound-id
                                (typecheck* named-expr type-env)
                                type-env))]
    [(If cond-expr then-expr else-expr)
    (typecheck cond-expr (BoolT) type-env)
    (let ([type (typecheck* then-expr type-env)])
      (typecheck else-expr type type-env) ; enforce same type
      type)]))

;; Evaluator and related types and helpers

(define-type ENV
  [EmptyEnv]
  [Extend Symbol VAL ENV])

(define-type VAL
  [NumV  Number]
  [BoolV Boolean]
  [FunV  Symbol PICKY ENV])

(: lookup : Symbol ENV -> VAL)
;; lookup a symbol in an environment, return its value or throw an
;; error if it isn't bound
(define (lookup name env)
  (cases env
    [(EmptyEnv) (error 'lookup "no binding for ~s" name)]
    [(Extend id val rest-env)
    (if (eq? id name) val (lookup name rest-env))]))

(: strip-numv : Symbol VAL -> Number)
;; converts a VAL to a Racket number if possible, throws an error if
;; not using the given name for the error message
(define (strip-numv name val)
  (cases val
    [(NumV n) n]
    ;; this error will never be reached, see below for more
    [else (error name "expected a number, got: ~s" val)]))

(: arith-op : (Number Number -> Number) VAL VAL -> VAL)
;; gets a Racket numeric binary operator, and uses it within a NumV
;; wrapper
(define (arith-op op val1 val2)
  (NumV (op (strip-numv 'arith-op val1)
            (strip-numv 'arith-op val2))))

(: bool-op : (Number Number -> Boolean) VAL VAL -> VAL)
;; gets a Racket numeric binary predicate, and uses it
;; within a BoolV wrapper
(define (bool-op op val1 val2)
  (BoolV (op (strip-numv 'bool-op val1)
            (strip-numv 'bool-op val2))))

(: eval : PICKY ENV -> VAL)
;; evaluates PICKY expressions by reducing them to values
(define (eval expr env)
  (cases expr
    [(Num n) (NumV n)]
    [(Id name) (lookup name env)]
    [(Add  l r) (arith-op + (eval l env) (eval r env))]
    [(Sub  l r) (arith-op - (eval l env) (eval r env))]
    [(Equal l r) (bool-op  = (eval l env) (eval r env))]
    [(Less  l r) (bool-op  < (eval l env) (eval r env))]
    [(Fun bound-id in-type bound-body)
    ;; note that types are not used at runtime,
    ;; so they're not stored in the closure
    (FunV bound-id bound-body env)]
    [(Call fun-expr arg-expr)
    (let ([fval (eval fun-expr env)])
      (cases fval
        [(FunV bound-id bound-body f-env)
          (eval bound-body
                (Extend bound-id (eval arg-expr env) f-env))]
        ;; `cases' requires complete coverage of all variants, but
        ;; this `else' is never used since we typecheck programs
        [else (error 'eval "`call' expects a function, got: ~s"
                            fval)]))]
    [(With bound-id named-expr bound-body)
    (eval bound-body (Extend bound-id (eval named-expr env) env))]
    [(If cond-expr then-expr else-expr)
    (let ([bval (eval cond-expr env)])
      (if (cases bval
            [(BoolV b) b]
            ;; same as above: this case is never reached
            [else (error 'eval "`if' expects a boolean, got: ~s"
                                bval)])
        (eval then-expr env)
        (eval else-expr env)))]))

(: run : String -> Number)
;; evaluate a PICKY program contained in a string
(define (run str)
  (let ([prog (parse str)])
    (typecheck prog (NumT) (EmptyTypeEnv))
    (let ([result (eval prog (EmptyEnv))])
      (cases result
        [(NumV n) n]
        ;; this error is never reached, since we make sure
        ;; that the program always evaluates to a number above
        [else (error 'run "evaluation returned a non-number: ~s"
                          result)]))))

;; tests -- including translations of the FLANG tests
(test (run "5") => 5)
(test (run "{fun {x : Num} {+ x 1}}") =error> "type error")
(test (run "{call {fun {x : Num} {+ x 1}} 4}") => 5)
(test (run "{with {x 3} {+ x 1}}") => 4)
(test (run "{with {identity {fun {x : Num} x}} {call identity 1}}")
      => 1)
(test (run "{with {add3 {fun {x : Num} {+ x 3}}}
              {call add3 1}}")
      => 4)
(test (run "{with {add3 {fun {x : Num} {+ x 3}}}
              {with {add1 {fun {x : Num} {+ x 1}}}
                {with {x 3}
                  {call add1 {call add3 x}}}}}")
      => 7)
(test (run "{with {identity {fun {x : {Num -> Num}} x}}
              {with {foo {fun {x : Num} {+ x 1}}}
                {call {call identity foo} 123}}}")
      => 124)
(test (run "{with {x 3}
              {with {f {fun {y : Num} {+ x y}}}
                {with {x 5} {call f 4}}}}")
      => 7)
(test (run "{call {with {x 3} {fun {y : Num} {+ x y}}} 4}")
      => 7)
(test (run "{with {f {with {x 3} {fun {y : Num} {+ x y}}}}
              {with {x 100}
                {call f 4}}}")
      => 7)
(test (run "{call {call {fun {x : {Num -> {Num -> Num}}} {call x 1}}
                        {fun {x : Num} {fun {y : Num} {+ x y}}}}
                  123}")
      => 124)
(test (run "{call {fun {x : Num} {if {< x 2} {+ x 5} {+ x 6}}} 1}")
      => 6)
(test (run "{call {fun {x : Num} {if {< x 2} {+ x 5} {+ x 6}}} 2}")
      => 8)

Finally, an obvious question is whether we can get rid of all of the type declarations. The main point here is that we need to somehow be able to typecheck expressions and assign “temporary types” to them that will later on change — for example, when we typecheck this:

{with {identity {fun {x} x}}
  {call identity 1}}

we need to somehow decide that the named expression has a general function type, with no commitment on the actual input and output types — and then change them after we typecheck the body. (We could try to resolve that somehow by typechecking the body first, but that will not work, since the body must be checked with some type assigned to the identifier, or it will fail.)

This can be done using type variables — things that contain boxes that can be used to change types as typecheck progresses. The following version does that. (Also, it gets rid of the typecheck* thing, since it can be achieved by using a type-variable and a call to typecheck.) Note the interesting tests at the end.

;;; ---<<<PICKY3>>>-------------------------------------------------
;; The Picky interpreter, no explicit types

#lang pl

#|
The grammar:
  <PICKY> ::= <num>
            | <id>
            | { + <PICKY> <PICKY> }
            | { - <PICKY> <PICKY> }
            | { = <PICKY> <PICKY> }
            | { < <PICKY> <PICKY> }
            | { fun { <id> } <PICKY> }
            | { call <PICKY> <PICKY> }
            | { with { <id> <PICKY> } <PICKY> }
            | { if <PICKY> <PICKY> <PICKY> }

The types are no longer part of the input syntax.

Evaluation rules:
  eval(N,env)                = N
  eval(x,env)                = lookup(x,env)
  eval({+ E1 E2},env)        = eval(E1,env) + eval(E2,env)
  eval({- E1 E2},env)        = eval(E1,env) - eval(E2,env)
  eval({= E1 E2},env)        = eval(E1,env) = eval(E2,env)
  eval({< E1 E2},env)        = eval(E1,env) < eval(E2,env)
  eval({fun {x} E},env)      = <{fun {x} E}, env>
  eval({call E1 E2},env1)
          = eval(Ef,extend(x,eval(E2,env1),env2))
                            if eval(E1,env1) = <{fun {x} Ef}, env2>
          = error!          otherwise -- but this doesn't happen
  eval({with {x E1} E2},env) = eval(E2,extend(x,eval(E1,env),env))
  eval({if E1 E2 E3},env)    = eval(E2,env)  if eval(E1,env) is true
                            = eval(E3,env)  otherwise

Type checking rules (note the ambiguity of the `fun' rule):

  Γ ⊢ n : Number

  Γ ⊢ x : Γ(x)

  Γ ⊢ A : Number  Γ ⊢ B : Number
  ———————————————————————————————
      Γ ⊢ {+ A B} : Number

  Γ ⊢ A : Number  Γ ⊢ B : Number
  ———————————————————————————————
      Γ ⊢ {< A B} : Boolean

            Γ[x:=τ₁] ⊢ E : τ₂
  ——————————————————————————————————————
  Γ ⊢ {fun {x} E} : (τ₁ -> τ₂)

  Γ ⊢ F : (τ₁ -> τ₂)  Γ ⊢ V : τ₁
  ——————————————————————————————
      Γ ⊢ {call F V} : τ₂

  Γ ⊢ C : Boolean  Γ ⊢ T : τ  Γ ⊢ E : τ
  ———————————————————————————————————————
            Γ ⊢ {if C T E} : τ

  Γ ⊢ V : τ₁  Γ[x:=τ₁] ⊢ E : τ₂
  ——————————————————————————————
  Γ ⊢ {with {x V} E} : τ₂

|#

(define-type PICKY
  [Num  Number]
  [Id    Symbol]
  [Add  PICKY PICKY]
  [Sub  PICKY PICKY]
  [Equal PICKY PICKY]
  [Less  PICKY PICKY]
  [Fun  Symbol PICKY] ; no types even here
  [Call  PICKY PICKY]
  [With  Symbol PICKY PICKY]
  [If    PICKY PICKY PICKY])

(: parse-sexpr : Sexpr -> PICKY)
;; parses s-expressions into PICKYs
(define (parse-sexpr sexpr)
  (match sexpr
    [(number: n)    (Num n)]
    [(symbol: name) (Id name)]
    [(list '+ lhs rhs) (Add  (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '- lhs rhs) (Sub  (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '= lhs rhs) (Equal (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list '< lhs rhs) (Less  (parse-sexpr lhs) (parse-sexpr rhs))]
    [(list 'call fun arg)
                      (Call  (parse-sexpr fun) (parse-sexpr arg))]
    [(list 'if c t e)
    (If (parse-sexpr c) (parse-sexpr t) (parse-sexpr e))]
    [(cons 'fun more)
    (match sexpr
      [(list 'fun (list (symbol: name)) body)
        (Fun name (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `fun' syntax in ~s" sexpr)])]
    [(cons 'with more)
    (match sexpr
      [(list 'with (list (symbol: name) named) body)
        (With name (parse-sexpr named) (parse-sexpr body))]
      [else (error 'parse-sexpr "bad `with' syntax in ~s" sexpr)])]
    [else (error 'parse-sexpr "bad expression syntax: ~s" sexpr)]))

(: parse : String -> PICKY)
;; parses a string containing a PICKY expression to a PICKY AST
(define (parse str)
  (parse-sexpr (string->sexpr str)))

;; Typechecker and related types and helpers

;; this is not a part of the AST now, and it also has a new variant
;; for type variables (see `same-type' for how it's used)
(define-type TYPE
  [NumT]
  [BoolT]
  [FunT TYPE TYPE]
  [?T (Boxof (U TYPE #f))])

;; this is similar to ENV, but it holds type information for the
;; identifiers during typechecking
(define-type TYPEENV
  [EmptyTypeEnv]
  [ExtendTypeEnv Symbol TYPE TYPEENV])

(: type-lookup : Symbol TYPEENV -> TYPE)
;; similar to `lookup' for type environments; note that the
;; error is phrased as a typecheck error, since this indicates
;; a failure at the type checking stage
(define (type-lookup name typeenv)
  (cases typeenv
    [(EmptyTypeEnv) (error 'typecheck "no binding for ~s" name)]
    [(ExtendTypeEnv id type rest-env)
    (if (eq? id name) type (type-lookup name rest-env))]))

(: typecheck : PICKY TYPE TYPEENV -> Void)
;; Checks that the given expression has the specified type.
;; Used only for side-effects, so return a void value.  There
;; are two side-effects that it can do: throw an error if the
;; input expression doesn't typecheck, and type variables can
;; be mutated once their values are known -- this is done by
;; the `types=' utility function that follows.
(define (typecheck expr type type-env)
  ;; convenient helpers
  (: type= : TYPE -> Void)
  (define (type= type2) (types= type type2 expr))
  (: two-nums : PICKY PICKY -> Void)
  (define (two-nums e1 e2)
    (typecheck e1 (NumT) type-env)
    (typecheck e2 (NumT) type-env))
  (cases expr
    [(Num n)    (type= (NumT))]
    [(Id name)  (type= (type-lookup name type-env))]
    [(Add  l r) (type= (NumT))  (two-nums l r)] ; note that the
    [(Sub  l r) (type= (NumT))  (two-nums l r)] ; order in these
    [(Equal l r) (type= (BoolT)) (two-nums l r)] ; things can be
    [(Less  l r) (type= (BoolT)) (two-nums l r)] ; swapped...
    [(Fun bound-id bound-body)
    (let (;; the identity of these type variables is important!
          [itype (?T (box #f))]
          [otype (?T (box #f))])
      (type= (FunT itype otype))
      (typecheck bound-body otype
                  (ExtendTypeEnv bound-id itype type-env)))]
    [(Call fun arg)
    (let ([type2 (?T (box #f))]) ; same here
      (typecheck arg type2 type-env)
      (typecheck fun (FunT type2 type) type-env))]
    [(With bound-id named-expr bound-body)
    (let ([type2 (?T (box #f))]) ; and here
      (typecheck named-expr type2 type-env)
      (typecheck bound-body type
                  (ExtendTypeEnv bound-id type2 type-env)))]
    [(If cond-expr then-expr else-expr)
    (typecheck cond-expr (BoolT) type-env)
    (typecheck then-expr type type-env)
    (typecheck else-expr type type-env)]))

(: types= : TYPE TYPE PICKY -> Void)
;; Compares the two input types, and throw an error if they don't
;; match.  This function is the core of `typecheck', and it is used
;; only for its side-effect.  Another side effect in addition to
;; throwing an error is when type variables are present -- they will
;; be mutated in an attempt to make the typecheck succeed.  Note
;; that the two type arguments are not symmetric: the first type is
;; the expected one, and the second is the one that the code implies
;; -- but this matters only for the error messages.  Also, the
;; expression input is used only for these errors.  As the code
;; clearly shows, the main work is done by `same-type' below.
(define (types= type1 type2 expr)
  (unless (same-type type1 type2)
    (error 'typecheck "type error for ~s: expecting ~a, got ~a"
          expr (type->string type1) (type->string type2))))

(: type->string : TYPE -> String)
;; Convert a TYPE to a human readable string,
;; used for error messages
(define (type->string type)
  (format "~s" type)
  ;; The code below would be useful, but unfortunately it doesn't
  ;; work in some cases.  To see the problem, try to run the example
  ;; below that applies identity on itself.  It's left here so you
  ;; can try it out when you're not running into this problem.
  #|
  (cases type
    [(NumT)  "Num"]
    [(BoolT) "Bool"]
    [(FunT i o)
    (string-append (type->string i) " -> " (type->string o))]
    [(?T box)
    (let ([t (unbox box)])
      (if t (type->string t) "?"))])
  |#)

;; Convenience type to make it possible to have a single `cases'
;; dispatch on two types instead of nesting `cases' in each branch
(define-type 2TYPES [PairT TYPE TYPE])

(: same-type : TYPE TYPE -> Boolean)
;; Compares the two input types, return true or false whether
;; they're the same.  The process might involve mutating type
;; variables.
(define (same-type type1 type2)
  ;; the `PairT' type is only used to conveniently match on both
  ;; types in a single `cases', it's not used in any other way
  (cases (PairT type1 type2)
    ;; flatten the first type, or set it to the second if it's unset
    [(PairT (?T box) type2)
    (let ([t1 (unbox box)])
      (if t1
        (same-type t1 type2)
        (begin (set-box! box type2) #t)))]
    ;; do the same for the second (reuse the above case)
    [(PairT type1 (?T box)) (same-type type2 type1)]
    ;; the rest are obvious
    [(PairT (NumT) (NumT)) #t]
    [(PairT (BoolT) (BoolT)) #t]
    [(PairT (FunT i1 o1) (FunT i2 o2))
    (and (same-type i1 i2) (same-type o1 o2))]
    [else #f]))

;; Evaluator and related types and helpers

(define-type ENV
  [EmptyEnv]
  [Extend Symbol VAL ENV])

(define-type VAL
  [NumV  Number]
  [BoolV Boolean]
  [FunV  Symbol PICKY ENV])

(: lookup : Symbol ENV -> VAL)
;; lookup a symbol in an environment, return its value or throw an
;; error if it isn't bound
(define (lookup name env)
  (cases env
    [(EmptyEnv) (error 'lookup "no binding for ~s" name)]
    [(Extend id val rest-env)
    (if (eq? id name) val (lookup name rest-env))]))

(: strip-numv : Symbol VAL -> Number)
;; converts a VAL to a Racket number if possible, throws an error if
;; not using the given name for the error message
(define (strip-numv name val)
  (cases val
    [(NumV n) n]
    ;; this error will never be reached, see below for more
    [else (error name "expected a number, got: ~s" val)]))

(: arith-op : (Number Number -> Number) VAL VAL -> VAL)
;; gets a Racket numeric binary operator, and uses it within a NumV
;; wrapper
(define (arith-op op val1 val2)
  (NumV (op (strip-numv 'arith-op val1)
            (strip-numv 'arith-op val2))))

(: bool-op : (Number Number -> Boolean) VAL VAL -> VAL)
;; gets a Racket numeric binary predicate, and uses it
;; within a BoolV wrapper
(define (bool-op op val1 val2)
  (BoolV (op (strip-numv 'bool-op val1)
            (strip-numv 'bool-op val2))))

(: eval : PICKY ENV -> VAL)
;; evaluates PICKY expressions by reducing them to values
(define (eval expr env)
  (cases expr
    [(Num n) (NumV n)]
    [(Id name) (lookup name env)]
    [(Add  l r) (arith-op + (eval l env) (eval r env))]
    [(Sub  l r) (arith-op - (eval l env) (eval r env))]
    [(Equal l r) (bool-op  = (eval l env) (eval r env))]
    [(Less  l r) (bool-op  < (eval l env) (eval r env))]
    [(Fun bound-id bound-body) (FunV bound-id bound-body env)]
    [(Call fun-expr arg-expr)
    (let ([fval (eval fun-expr env)])
      (cases fval
        [(FunV bound-id bound-body f-env)
          (eval bound-body
                (Extend bound-id (eval arg-expr env) f-env))]
        ;; `cases' requires complete coverage of all variants, but
        ;; this `else' is never used since we typecheck programs
        [else (error 'eval "`call' expects a function, got: ~s"
                            fval)]))]
    [(With bound-id named-expr bound-body)
    (eval bound-body (Extend bound-id (eval named-expr env) env))]
    [(If cond-expr then-expr else-expr)
    (let ([bval (eval cond-expr env)])
      (if (cases bval
            [(BoolV b) b]
            ;; same as above: this case is never reached
            [else (error 'eval "`if' expects a boolean, got: ~s"
                                bval)])
        (eval then-expr env)
        (eval else-expr env)))]))

(: run : String -> Number)
;; evaluate a PICKY program contained in a string
(define (run str)
  (let ([prog (parse str)])
    (typecheck prog (NumT) (EmptyTypeEnv))
    (let ([result (eval prog (EmptyEnv))])
      (cases result
        [(NumV n) n]
        ;; this error is never reached, since we make sure
        ;; that the program always evaluates to a number above
        [else (error 'run "evaluation returned a non-number: ~s"
                          result)]))))

;; tests -- including translations of the FLANG tests
(test (run "5") => 5)
(test (run "{fun {x} {+ x 1}}") =error> "type error")
(test (run "{call {fun {x} {+ x 1}} 4}") => 5)
(test (run "{with {x 3} {+ x 1}}") => 4)
(test (run "{with {identity {fun {x} x}} {call identity 1}}") => 1)
(test (run "{with {add3 {fun {x} {+ x 3}}} {call add3 1}}") => 4)
(test (run "{with {add3 {fun {x} {+ x 3}}}
              {with {add1 {fun {x} {+ x 1}}}
                {with {x 3}
                  {call add1 {call add3 x}}}}}")
      => 7)
(test (run "{with {identity {fun {x} x}}
              {with {foo {fun {x} {+ x 1}}}
                {call {call identity foo} 123}}}")
      => 124)
(test (run "{with {x 3}
              {with {f {fun {y} {+ x y}}}
                {with {x 5} {call f 4}}}}")
      => 7)
(test (run "{call {with {x 3} {fun {y} {+ x y}}} 4}")
      => 7)
(test (run "{with {f {with {x 3} {fun {y} {+ x y}}}}
              {with {x 100}
                {call f 4}}}")
      => 7)
(test (run "{call {call {fun {x} {call x 1}}
                        {fun {x} {fun {y} {+ x y}}}}
                  123}")
      => 124)
(test (run "{call {fun {x} {if {< x 2} {+ x 5} {+ x 6}}} 1}") => 6)
(test (run "{call {fun {x} {if {< x 2} {+ x 5} {+ x 6}}} 2}") => 8)

;; Note that we still have a language with the same type system,
;; even though it looks like it could be more flexible -- for
;; example, the following two examples work:
(test (run "{with {identity {fun {x} x}}
              {call identity 1}}")
      => 1)
(test (run "{with {identity {fun {x} x}}
              {if {call identity {< 1 2}} 1 2}}")
      => 1)
;; but this doesn't, since identity can not be used with different
;; types:
(test (run "{with {identity {fun {x} x}}
              {if {call identity {< 1 2}}
                {call identity 1}
                2}}")
      =error> "type error")
;; this doesn't work either -- with an interesting error message:
(test (run "{with {identity {fun {x} x}}
              {call {call identity identity} 1}}")
      =error> "type error")
;; ... but these two work fine:
(test (run "{with {identity1 {fun {x} x}}
              {with {identity2 {fun {x} x}}
                {+ {call identity1 1}
                  {if {call identity2 {< 1 2}} 1 2}}}}")
      => 2)
(test (run "{with {identity1 {fun {x} x}}
              {with {identity2 {fun {x} x}}
                {call {call identity1 identity2} 1}}}")
      => 1)

Here are two other interesting things to try out — in particular, the type that is shown in the error message is interesting:

(run "{fun {x} x}")
(run "{call {fun {x} {call x x}} {fun {x} {call x x}}}")

More specifically, it is interesting to try the following to see explicitly what our typechecker infers for {fun {x} {call x x}}:

> (define b (?T (box #f)))
> (typecheck (parse "{fun {x} {call x x}}") b (EmptyTypeEnv))
> (cases b [(?T b) (unbox b)] [else #f])
- : TYPE
(?T #&(FunT #0=(?T #&(FunT (?T #&#0#) #1=(?T #&#f))) #1#))

To see it clearly, we can replace each (?T #&...) with the ... that it contains:

(FunT #0=(FunT #0# #1=#f) #1#)

and to clarify further, convert the FunT to an infix -> and the #f to a <?> and use α for the unknown “type variable” that is represented by the #1 (which is used twice):

(#0=(#0# -> α) -> α)

This shows us that the type is recursive.

Sidenote#1: You can now go back to the code and look at type->string, which is an attempt to implement a nice string representation for types. Can you see now why it cannot work (at least not without more complex code)?

Sidenote#2: Compare the above with OCaml, which can infer such types when started with a -rectypes flag:

# let foo = fun x -> x x ;;
val foo : ('a -> 'b as 'a) -> 'b = <fun>

The type here is identical to our type: 'a and 'b should be read as α and β resp., and as is used in the same way that Racket shows a cyclic structure using #0#. As for the question of why OCaml doesn’t always behave as if the -rectypes flag is given, the answer is that its type checker might fall into the same trap that ours does — it gets stuck with:

# let foo = (fun x -> x x) (fun x -> x x) ;;

The α that we see here is “kind of” in a direction of something that resembles a polymorphic type, but we really don’t have polymorphism in our language: each box can be filled just one time with one type, and from then on that type is used in all further uses of the same box type. For example, note the type error we get with:

{with {f {fun {x} x}}
  {call f {< {call f 1} {call f 2}}}}

Typing RecursionWednesday, November 28th

We already know that without recursion life can be very boring… So we obviously want to be able to have recursive functions — but the question is how will they interact with our type system. One thing that we have seen is that by just having functions we get recursion. This was achieved by the Y combinator function. It seems like the same should apply to our simple typed language. The core of the Y combinator was using an expression similar to Omega that generates the infinite loop that is needed. In our language:

{call {fun {x} {call x x}} {fun {x} {call x x}}}

This expression was impossible to evaluate completely since it never terminates, but it served as a basis for the Y combinator so we need to be able to perform this kind of infinite loop. Now, consider the type of the first x — it’s used in a call expression as a function, so its type must be a function type, say τ₁->τ₂. In addition, its argument is x itself so its type is also τ₁ — this means that we have:

τ₁ -> τ₂ = τ₁

and from this we get:

=> τ₁ = τ₁ -> τ₂
      = (τ₁ -> τ₂) -> τ₂
      = ((τ₁ -> τ₂) -> τ₂) -> τ₂
      = ...

And this is a type that does not exist in our type system, since we can only have finite types. Therefore, we have a proof by contradiction that this expression cannot be typed in our system.

This is closely related to the fact that the typed language we have described so far is “strongly normalizing”: no matter what program you write, it will always terminate! To see this, very informally, consider this language without functions — this is clearly a language where all programs terminate, since the only way to create a loop is through function applications. Now add functions and function application — in the typing rules for the resulting language, each fun creates a function type (creates an arrow), and each function application consumes a function type (deletes one arrow) — since types are finite, the number of arrows is finite, which means that the number of possible applications is finite, so all programs must run in finite time.

Note that when we discussed how to type the Y combinator we needed to use a Rec constructor — something that the current type system has. Using that, we could have easily solve the τ₁ = τ₁ -> τ₂ equation with (Rec τ₁ (τ₁ -> τ₂)).

In the our language, therefore, the halting problem doesn’t even exist, since all programs (that are properly typed) are guaranteed to halt. This property is useful in many real-life situations (consider firewall rules, configuration files, devices with embedded code). But the language that we get is very limited as a result — we really want the power to shoot our feet…

Extending Picky with recursionWednesday, November 28th

As we have seen, our language is strongly normalizing, which means that to get general recursion, we must introduce a new construct (unlike previously, when we didn’t really need one). We can do this as we previously did — by adding a new construct to the language, or we can somehow extend the (sub) language of type descriptions to allow a new kind of type that can be used to solve the τ₁ = τ₁ -> τ₂ equation. An example of this solution would be similar to the Rec type constructor in Typed Racket: a new type constructor that allows a type to refer to itself — and using (Rec τ₁ (τ₁ -> τ₂)) as the solution. However, this complicates things: type descriptions are no longer unique, since we have Num, (Rec this Num), and (Rec this (Rec that Num)) that are all equal.

For simplicity we will now take the first route and add rec — an explicit recursive binder form to the language (as with with, we’re going back to rec rather than bindrec to keep things simple).

First, the new BNF:

<PICKY> ::= <num>
          | <id>
          | { + <PICKY> <PICKY> }
          | { < <PICKY> <PICKY> }
          | { fun { <id> : <TYPE> } : <TYPE> <PICKY> }
          | { call <PICKY> <PICKY> }
          | { with { <id> : <TYPE> <PICKY> } <PICKY> }
          | { rec { <id> : <TYPE> <PICKY> } <PICKY> }
          | { if <PICKY> <PICKY> <PICKY> }

<TYPE>  ::= Number
          | Boolean
          | ( <TYPE> -> <TYPE> )

We now need to add a typing judgment for rec expressions. What should it look like?

            ???
———————————————————————————
Γ ⊢ {rec {x : τ₁ V} E} : τ₂

rec is similar to all the other local binding forms, like with, it can be seen as a combination of a function and an application. So we need to check the two things that those rules checked — first, check that the body expression has the right type assuming that the type annotation given to x is valid:

  Γ[x:=τ₁] ⊢ E : τ₂  ???
———————————————————————————
Γ ⊢ {rec {x : τ₁ V} E} : τ₂

Now, we also want to add the other side — making sure that the τ₁ type annotation is valid:

Γ[x:=τ₁] ⊢ E : τ₂  Γ ⊢ V : τ₁
——————————————————————————————
Γ ⊢ {rec {x : τ₁ V} E} : τ₂

But that will not be possible in general — V is an expression that can include x itself — that’s the whole point. The conclusion is that we should use a similar trick to the one that we used to specify evaluation of recursive binders — the same environment is used for both the named expression and for the body expression:

Γ[x:=τ₁] ⊢ E : τ₂  Γ[x:=τ₁] ⊢ V : τ₁
—————————————————————————————————————
    Γ ⊢ {rec {x : τ₁ V} E} : τ₂

You can also see now that this rule adds an arrow type to the Γ type environment, in a way that makes it possible to use it over and over, making it possible to run infinite loops in this language.

Our complete language specification is below.

<PICKY> ::= <num>
          | <id>
          | { + <PICKY> <PICKY> }
          | { < <PICKY> <PICKY> }
          | { fun { <id> : <TYPE> } : <TYPE> <PICKY> }
          | { call <PICKY> <PICKY> }
          | { with { <id> : <TYPE> <PICKY> } <PICKY> }
          | { rec  { <id> : <TYPE> <PICKY> } <PICKY> }
          | { if <PICKY> <PICKY> <PICKY> }

<TYPE>  ::= Number
          | Boolean
          | ( <TYPE> -> <TYPE> )

Γ ⊢ n : Number

Γ ⊢ x : Γ(x)

Γ ⊢ A : Number  Γ ⊢ B : Number
———————————————————————————————
    Γ ⊢ {+ A B} : Number

Γ ⊢ A : Number  Γ ⊢ B : Number
———————————————————————————————
    Γ ⊢ {< A B} : Boolean

          Γ[x:=τ₁] ⊢ E : τ₂
——————————————————————————————————————
Γ ⊢ {fun {x : τ₁} : τ₂ E} : (τ₁ -> τ₂)

Γ ⊢ F : (τ₁ -> τ₂)  Γ ⊢ V : τ₁
——————————————————————————————
    Γ ⊢ {call F V} : τ₂

Γ ⊢ C : Boolean  Γ ⊢ T : τ  Γ ⊢ E : τ
———————————————————————————————————————
          Γ ⊢ {if C T E} : τ

Γ ⊢ V : τ₁  Γ[x:=τ₁] ⊢ E : τ₂
——————————————————————————————
Γ ⊢ {with {x : τ₁ V} E} : τ₂

Γ[x:=τ₁] ⊢ V : τ₁  Γ[x:=τ₁] ⊢ E : τ₂
—————————————————————————————————————
    Γ ⊢ {rec {x : τ₁ V} E} : τ₂

Typing DataWednesday, November 28th

PLAI §27

An important concept that we have avoided so far is user-defined types. This issue exists in practically all languages, including the ones we did so far, since a language without the ability to create new user-defined types is a language with a major problem. (As a side note, we did talk about mimicking an object system using plain closures, but it turns out that this is insufficient as a replacement for true user-defined types — you can kind of see that in the Schlac language, where the lack of all types mean that there is no type error.)

In the context of a statically typed language, this issue is even more important. Specifically, we talked about typing recursive code, but we should also consider typing recursive data. For example, we will start with a length function in an extension of the language that has empty?, rest, and NumCons and NumEmpty constructors:

{rec {length : ???
      {fun {l : ???} : Number
        {if {empty? l}
          0
          {+ 1 {call length {rest l}}}}}}
  {call length {NumCons 1 {NumCons 2 {NumCons 3 {NumEmpty}}}}}}

But adding all of these new functions as built-ins is getting messy: we want our language to have a form for defining new kinds of data. In this example — we want to be able to define the NumList type for lists of numbers. We therefore extend the language with a new with-type form for creating new user-defined types, using variants in a similar way to our own course language:

{with-type {NumList [NumEmpty]
                    [NumCons Number ???]}
  {rec {length : ???
        {fun {l : ???} : Number
          ...}}
    ...}}

We assume here that the NumList definition provides us with a number of new built-ins — NumEmpty and NumCons constructors, and assume also a cases form that can be used to both test a value and access its components (with the constructors serving as patterns). This makes the code a little different than what we started with:

{with-type {NumList [NumEmpty]
                    [NumCons Number ???]}
  {rec {length : ???
        {fun {l : ???} : Number
          {cases l
            [{NumEmpty}    0]
            [{NumCons x r} {+ 1 {call length r}}]}}}
    {call length {NumCons 1 {NumCons 2 {NumCons 3 {NumEmpty}}}}}}}

The question is what should the ??? be filled with? Clearly, recursive data types are very common and we need to support them. The scope of with-type should therefore be similar to rec, except that it works at the type level: the new type is available for its own definition. This is the complete code now:

{with-type {NumList [NumEmpty]
                    [NumCons Number NumList]}
  {rec {length : (NumList -> Number)
        {fun {l : NumList} : Number
          {cases l
            [{NumEmpty}    0]
            [{NumCons x r} {+ 1 {call length r}}]}}}
    {call length {NumCons 1 {NumCons 2 {NumCons 3 {NumEmpty}}}}}}}

(Note that in the course language we can do just that, and in addition, the Rec type constructor can be used to make up recursive types.)

An important property that we would like this type to have is for it to be well founded: that we’d never get stuck in some kind of type-level infinite loop. To see that this holds in this example, note that some of the variants are self-referential (only NumCons here), but there is at least one that is not (NumEmpty) — if there wasn’t any simple variant, then we would have no way to construct instances of this type to begin with!

[As a side note, if the language has lazy semantics, we could use such types — for example:

{with-type {NumList [NumCons Number NumList]}
  {rec {ones : NumList {NumCons 1 ones}}
    ...}}

Reasoning about such programs requires more than just induction though.]

Judgments for recursive typesThursday, November 29th

If we want to have a language that is basically similar to the course language, then — as seen above — we’d use a similar cases expression. How should we type-check such expressions? In this case, we want to verify this:

Γ ⊢ {cases l [{NumEmpty} 0]
            [{NumCons x r} {+ 1 {call length r}}]} : Number

Similarly to the judgment for if expressions, we require that the two result expressions are numbers. Indeed, you can think about cases as a more primitive tool that has the functionality of if — in other words, given such user-defined types we could implement booleans as a new type and and implement if using cases. For example, wrap programs with:

{with-type {Bool [True] [False]} ...}

and translate {if E1 E2 E3} to {cases E1 [{True} E2] [{False} E3]}.

Continuing with typing cases, we now have:

Γ ⊢ 0 : Number          Γ ⊢ {+ 1 {call length r}} : Number
————————————————————————————————————————————————————————————
Γ ⊢ {cases l [{NumEmpty} 0]
            [{NumCons x r} {+ 1 {call length r}}]} : Number

But this will not work — we have no type for r here, so we can’t prove the second subgoal. We need to consider the NumList type definition as something that, in addition to the new built-ins, provides us with type judgments for these built-ins. In the case of the NumCons variant, we know that using {NumCons x r} is a pattern that matches NumList values that are a result of this variant constructor but it also binds x and r to the values of the two fields, and since all uses of the constructor are verified, the fields have the declared types. This means that we need to extend Γ in this rule so we’re able to prove the two subgoals. Note that we do the same for the NumEmpty case, except that there are no new bindings there.

Γ ⊢ 0 : Number
Γ[x:=Number; r:=NumList] ⊢ {+ 1 {call length r}} : Number
————————————————————————————————————————————————————————————
Γ ⊢ {cases l [{NumEmpty} 0]
            [{NumCons x r} {+ 1 {call length r}}]} : Number

Finally, we need to verify that the value itself — l — has the right type: that it is a NumList.

Γ ⊢ l : NumList
Γ ⊢ 0 : Number
Γ[x:=Number; r:=NumList] ⊢ {+ 1 {call length r}} : Number
————————————————————————————————————————————————————————————
Γ ⊢ {cases l [{NumEmpty} 0]
            [{NumCons x r} {+ 1 {call length r}}]} : Number

But why NumList and not some other defined type? This judgment needs to do a little more work: it should inspect all of the variants that are used in the branches, find the type that defines them, then use that type as the subgoal. Furthermore, to make the type checker more useful, it can check that we have complete coverage of the variants, and that no variant is used twice:

Γ ⊢ l : NumList
    (also need to show that NumEmpty and NumCons are all of the
    variants of NumList, with no repetition.)
Γ ⊢ 0 : Number
Γ[x:=Number; r:=NumList] ⊢ {+ 1 {call length r}} : Number
————————————————————————————————————————————————————————————
Γ ⊢ {cases l [{NumEmpty} 0]
            [{NumCons x r} {+ 1 {call length r}}]} : Number

Note that how this is different from the version in the textbook — it has a type-case expression with the type name mentioned explicitly — for example: {type-case l NumList {{NumEmpty} 0} ...}. This is essentially the same as having each defined type come with its own cases expression. Our rule needs to do a little more work, but overall it is a little easier to use. (And the same goes for the actual implementation of the two languages.)

In addition to cases, we should also have typing judgments for the constructors. These are much simpler, for example:

Γ ⊢ x : Number  Γ ⊢ r : NumList
————————————————————————————————
  Γ ⊢ {NumCons x r} : NumList

Alternatively, we could add the constructors as new functions instead of new special forms — so in the Picky language they’d be used in call expressions. The with-type will then create the bindings for its scope at runtime, and for the typechecker it will add the relevant types to Γ:

Γ[NumCons:=(Number NumList -> NumList); NumEmpty:=(-> NumList)]

(This requires functions of any arity, of course.) Using accessor functions could be similarly simpler than cases, but less convenient for users.

Note about representation: a by-product of our type checker is that whenever we have a NumList value, we know that it must be an instance of either NumEmpty or NumCons. Therefore, we could represent such values as a wrapped value container, with a single bit that distinguishes the two. This is in contrast to dynamically typed languages like Racket, where every new type needs to have its own globally unique tag.

“Runaway” instancesThursday, November 29th

Consider this code:

{with-type {NumList [NumEmpty] ...} {NumEmpty}}

We now know how to type check its validity, but what about the type of this whole expression? The obvious choice would be NumList:

{with-type {NumList [NumEmpty] ...} {NumEmpty}} : NumList

There is a subtle but important problem here: the expression evaluates to a NumList, but we can no longer use this value, since we’re out of the scope of the NumList type definition! In other words, we would typecheck a program that is pretty much useless.

Even if we were to allow such a value to flow to a different context with a NumList type definition, we wouldn’t want the two to be confused — following the principle of lexical scope, we’d want each type definition to be unique to its own scope even if it has the same concrete name. For example, using NumList as the type of the inner with-type here:

{with-type {NumList something-completely-different}
  {with-type {NumList [NumEmpty] ...}
    {NumEmpty}}}

would make it wrong.

(In fact, we might want to have a new type even if the value goes outside of this scope and back in. The default struct definitions in Racket have exactly this property — they’re generative — which means that each “call” to define-struct creates a new type, so:

(define (two-foos)
  (define (foo x)
    (struct foo (x))
    (foo x))
  (list (foo 1) (foo 2)))

returns two instances of two different foo types!)

One way to resolve this is to just forbid the type from escaping the scope of its definition — so we would forbid the type of the expression from being NumList, which makes

{with-type {NumList [NumEmpty] ...} {NumEmpty}} : NumList

invalid. But that’s not enough — what about returning a compound value that contains an instance of NumList? For example — what if we return a list or a function with a NumList instance?

{with-type {NumList [NumEmpty] ...}
  {fun {x} {NumEmpty}}} : Num -> NumList??

Obviously, we would need to extend this restriction: the resulting type should not mention the defined type at all — not even in lists or functions or anything else. This is actually easy to do: if the overall expression is type-checked in the surrounding lexical scope, then it is type-checked in the surrounding type environment (Γ), and that environment has nothing in it about NumList (well, nothing about this NumList).

Note that this is, very roughly speaking, what our course language does: define-type can only define new types when it is used at the top-level.

This works fine with the above assumption that such a value would be completely useless — but there are aspects of such values that are useful. Such types are close to things that are known as “existential types”, and they are for defining opaque values that you can do nothing with except pass them around, and only code in a specific lexical context can actually use them. For example, you could lump together the value with a function that can work on this value. If it wasn’t for the define-type top-level restriction, we could write the following:

(: foo : Integer -> (List ??? (??? -> Integer)))
(define (foo x)
  (define-type FOO [Foo Integer])
  (list (Foo 1)
        (lambda (f)
          (cases f [(Foo n) (* n n)]))))

There is nothing that we can do with resulting Foo instance (we don’t even have a way to name it) — but in the result of the above function we get also a function that could work on such values, even ones from different calls:

((second (foo 1)) (first (foo 2))) -> 4

Since such kind of values are related to hiding information, they’re useful (among other things) when talking about module systems (and object systems), where you want to have a local scope for a piece of code with bindings that are not available outside it.

Type soundnessThursday, November 29th

PLAI §28

Having a type checker is obviously very useful — but to be able to rely on it, we need to provide some kind of a formal account of the kind of guarantees that we get by using one. Specifically, we want to guarantee that a program that type-checks is guaranteed to never fail with a type error. Such type errors in Racket result in an exception — but in C they can result in anything. In our simple Picky implementation, we still need to check the resulting value in run:

(typecheck prog (NumT) (EmptyTypeEnv))
(let ([result (eval prog (EmptyEnv))])
  (cases result
    [(NumV n) n]
    ;; this error is never reached, since we make sure
    ;; that the program always evaluates to a number above
    [else (error 'run "evaluation returned a non-number: ~s"
                      result)]))

A soundness proof for this would show that checking the result (in cases) is not needed. However, the check must be there since Typed Racket (or any other typechecker) is far from making up and verifying such a proof by itsef.

In this context we have a specific meaning for “fail with a type error”, but these failures can be very different based on the kind of properties that your type checker verifies. This property of a type system is called soundness: a sound type system is one that will never allow such errors for type-checked code:

For any program p, if we can type-check p : τ, then p will evaluate to a value that is in the type τ.

The importance of this can be seen in that it is the only connection between the type system and code execution. Without it, a type system is a bunch of syntactic rules that are completely disconnected from how the program runs. (Note also that — “in the type” — works for the (common) case where types are sets of values.)

But this statement isn’t exactly what we need — it states a property that is too strong: what if execution gets stuck in an infinite loop? (That wasn’t needed before we introduced rec, where we could extend the conclusion part to: “… then p will terminate and evaluate to a value that is in the type τ”.) We therefore need to revise it:

For any program p, if we can type-check p : τ, and if p terminates and returns v, then v is in the type τ.

But there are still problems with this. Some programs evaluate to a value, some get stuck in an infinite loop, and some … throw an error. Even with type checking, there are still cases when we get runtime errors. For example, in practically all statically typed languages the length of a list is not encoded in its type, so {first null} would throw an error. (It’s possible to encode more information like that in types, but there is a downside to this too: putting more information in the type system means that things get less flexible, and it becomes more difficult to write programs since you’re moving towards proving more facts about them.)

Even if we were to encode list lengths in the type, we would still have runtime errors: opening a missing file, writing to a read-only file fetching a non-existent URL, etc, so we must find some way to account for these errors. Some “solutions” are:

So, assuming exceptions, we need to further refine what it means for a type system to be sound:

For any program p, if we can type-check p : τ, and if p terminates without exceptions and returns v, then v is in the type τ.

An important thing to note here is that languages can have very different ideas about where to raise an exception. For example, Scheme implementations often have a trivial type-checker and throw runtime exceptions when there is a type error. On the other hand, there are systems that express much more in their type system, leaving much less room for runtime exceptions.

A soundness proof ties together a particular type system with the statement that it is sound. As such, it is where you tie the knot between type checking (which happens at the syntactic level) and execution (dealing with runtime values). These are two things that are usually separate — we’ve seen throughout the course many examples for things that could be done only at runtime, and things that should happen completely on the syntax. eval is the important semantic function that connects the two worlds (compile also did this, when we converted our evaluator to a compiler) — and in here, it is the soundness proof that makes the connection.

To demonstrate the kind of differences between the two sides, consider an if expression — when it is executed, only one branch is evaluated, and the other is irrelevant, but when we check its type, both sides need to be verified. The same goes for a function whose execution get stuck in an infinite loop: the type checker will not get into a loop since it is not executing the code, only scans the (finite) syntax.

The bottom line here is that type soundness is really a claim that the type system provides some guarantees about the runtime behavior of programs, and its proof demonstrates that these guarantees do hold. A fundamental problem with the type system of C and C++ is that it is not sound: these languages have a type system, but it does not provide such runtime guarantees. (In fact, C is even worse in that it really has two type systems: there is the system that C programmers usually interact with, which has a conventional set of type — including even higher-order function types; and there is the machine-level type system, which only talks about various bit lengths of data. For example, using “%s” in a printf() format string will blindly copy characters from the address pointed to by the argument until it reaches a 0 character — even if the actual argument is really a floating point number or a function.)

Note that people often talk about “strongly typed languages”. This term is often meaningless in that different people take it to mean different things: it is sometimes used for a language that “has a static type checker”, or a language that “has a non-trivial type checker”, and sometimes it means that a language has a sound type system. For most people, however, it means some vague idea like “a language like C or Pascal or Java” rather than some concrete definition.

Explicit polymorphismThursday, November 29th

PLAI §29

Consider the length definition that we had — it is specific for NumLists, so rename it to lengthNum:

{with-type {NumList ...}
  {rec {lengthNum : (NumList -> Num)
        {fun {l : NumList} : Num
          {cases l
            [{NumEmpty}    0]
            [{NumCons x r} {+ 1 {call lengthNum r}}]}}}
    {call lengthNum
          {NumCons 1 {NumCons 2 {NumCons 3 {NumEmpty}}}}}}}

To simplify things, assume that types are previously defined, and that we have an even more Racket-like language where we simply write a define form:

{define lengthNum
  {fun {l : NumList} : Num
    {cases l
      [{NumEmpty}    0]
      [{NumCons x r} {+ 1 {call lengthNum r}}]}}}

What would happen if, for example, we want to take the length of a list of booleans? We won’t be able to use the above code since we’d get a type error. Instead, we’d need a separate definition for the other kind of length:

{define lengthBool
  {fun {l : BoolList} : Num
    {cases l
      [{BoolEmpty}    0]
      [{BoolCons x r} {+ 1 {call lengthBool r}}]}}}

We’ve designed a statically typed language that is effective in catching a large number of errors, but it turns out that it’s too restrictive — we cannot implement a single generic length function. Given that our type system allows an infinite number of types, this is a major problem, since every new type that we’ll want to use in a list requires writing a new definition for a length function that is specific to this type.

One way to address the problem would be to somehow add a new length primitive function, with specific type rules to make it apply to all possible types. (Note that the same holds for the list type too — we need a new type definition for each of these, so this solution implies a new primitive type that will do the same generic trick.) This is obviously a bad idea: there are other functions that will need the same treatment (append, reverse, map, fold, etc), and there are other types with similar problems (any new container type). A good language should allow writing such a length function inside the language, rather than changing the language for every new addition.

Going back to the code, a good question to ask is what is it exactly that is different between the two length functions? The answer is that there’s very little that is different. To see this, we can take the code and replace all occurrences of Num or Bool by some ???. Even better — this is actually abstracting over the type, so we can use a familiar type variable, τ:

{define length〈τ〉
  {fun {l : 〈τ〉List} : Num
    {cases l
      [{〈τ〉Empty}    0]
      [{〈τ〉Cons x r} {+ 1 {call length〈τ〉 r}}]}}}

This is a kind of a very low-level “abstraction” — we replace parts of the text — parts of identifiers — with a kind of a syntactic meta variable. But the nature of this abstraction is something that should look familiar — it’s abstracting over the code, so it’s similar to a macro. It’s not really a macro in the usual sense — making it a real macro involves answering questions like what does length evaluate to (in the macro system that we’ve seen, a macro is not something that is a value in itself), and how can we use these macros in the cases patterns. But still, the similarity should provide a good intuition about what goes on — and in particular the basic fact is the same: this is an abstraction that happens at the syntax level, since typechecking is something that happens at that level.

To make things more manageable, we’ll want to avoid the abstraction over parts of identifiers, so we’ll move all of the meta type variables, and make them into arguments, using 〈...〉 brackets to stand for “meta level applications”:

{define length〈τ〉
  {fun {l : List〈τ〉} : Num
    {cases l
      [{Empty〈τ〉}    0]
      [{Cons〈τ〉 x r} {+ 1 {call length〈τ〉 r}}]}}}

Now, the first “〈τ〉” is actually a kind of an input to length, it’s a binding that has the other τs in its scope. So we need to have the syntax reflect this somehow — and since fun is the way that we write such abstractions, it seems like a good choice:

{define length
  {fun {τ}
    {fun {l : List〈τ〉} : Num
      {cases l
        [{Empty〈τ〉}    0]
        [{Cons〈τ〉 x r} {+ 1 {call length〈τ〉 r}}]}}}}

But this is very confused and completely broken. The new abstraction is not something that is implemented as a function — otherwise we’ll need to somehow represent type values within our type system. (Trying that has some deep problems — for example, if we have such type values, then it needs to have a type too; and if we add some Type for this, then Type itself should be a value — one that has itself as its type!)

So instead of fun, we need a new kind of a syntactic, type-level abstraction. This is something that is acts as a function that gets used by the type checker. The common way to write such functions is with a capital lambdaΛ. Since we already use Greek letters for things that are related to types, we’ll use that as is (again, with “〈〉“s), instead of a confusing capitalized Lambda (or a similarly confusing Fun):

{define length
  〈Λ 〈τ〉
    {fun {l : List〈τ〉} : Num
      {cases l
        [{Empty〈τ〉}    0]
        [{Cons〈τ〉 x r} {+ 1 {call length〈τ〉 r}}]}}〉}

and to use this length we’ll need to instantiate it with a specific type:

{+ {call length〈Num〉 {list 1 2}}
  {call length〈Bool〉 {list #t #f}}}

Note that we have several kinds of meta-applications, with slightly different intentions:

Actually, the last item points at one way in which the above sample calls:

{+ {call length〈Num〉 {list 1 2}}
  {call length〈Bool〉 {list #t #f}}}

are broken — we should also have a type argument for list:

{+ {call length〈Num〉 {list〈Num〉 1 2}}
  {call length〈Bool〉 {list〈Bool〉 #t #f}}}

or, given that we’re in the limited picky language:

{+ {call length〈Num〉 {cons〈Num〉 1 {cons〈Num〉 2 null〈Num〉}}}
  {call length〈Bool〉 {cons〈Bool〉 #t {cons〈Bool〉 #f null〈Bool〉}}}}

Such a language is called “parametrically polymorphic with explicit type parameters” — it’s polymorphic since it applies to any type, and it’s explicit since we have to specify the types in all places.

Polymorphism in the type description languageThursday, November 29th

Given our definition for length, the type of length〈Num〉 is obvious:

length〈Num〉 : List〈Num〉 -> Num

but what would be the type of length by itself? If it was a function (which was a broken idea we’ve seen), then we would write:

length : τ -> (List〈τ〉 -> Num)

But this is broken in the same way: the first arrow is fundamentally different than the second — one is used for a Λ, and the other for a fun. In fact, the arrows are even more different, because the two τs are very different: the first one binds the second. So the first arrow is bogus — instead of an arrow we need some way to say that this is a type that “for all τ” is “List〈τ〉 -> Num”. The common way to write this should be very familiar:

length : ∀τ. List〈τ〉 -> Num

Finally, τ is usually used as a meta type variable; for these types the convention is to use the first few Greek letters, so we get:

length : ∀α. List〈α〉 -> Num

And some more examples:

filter : ∀α. (α->Bool) × List〈α〉 -> List〈α〉
map : ∀α,β. (α->β) × List〈α〉 -> List〈β〉

where × stands for multiple arguments (which isn’t mentioned explicitly in Typed Racket).

Type judgments for explicit polymorphism and executionThursday, November 29th

Given our notation for polymorphic functions, it looks like we’re introducing a runtime overhead. For example, our length definition:

{define length
  〈Λ 〈α〉
    {fun {l : List〈α〉} : Num
      {cases l
        [{Empty〈α〉}    0]
        [{Cons〈α〉 x r} {+ 1 {call length〈α〉 r}}]}}〉}

looks like it now requires another curried call for each iteration through the list. This would be bad for two reasons: first, one of the main goals of static type checking is to avoid runtime work, so adding work is highly undesirable. An even bigger problem is that types are fundamentally a syntactic thing — they should not exist at runtime, so we don’t want to perform these type applications at runtime simply because we don’t want types to exist at runtime. If you think about it, then every traditional compiler that typechecks code does so while compiling, not when the resulting compiled program runs. (A recent exception in various languages are “dynamic” types that are used in a way that is similar to plain (untyped) Racket.)

This means that we want to eliminate these applications in the typechecker. Even better: instead of complicating the typechecker, we can begin by applying all of the type meta-applications, and get a result that does not have any such applications or any type variables left — then use the simple typechecker on the result. This process is called “type elaboration”.

As usual, there are two new formal rules for dealing with these abstractions — one for type abstractions and another for type applications. Starting from the latter:

  Γ ⊢ E : ∀α.τ
———————————————————
Γ ⊢ E〈τ₂〉 : τ[τ₂/α]

which means that when we encounter a type application E〈τ₂〉 where E has a polymorphic type ∀α.τ, then we substitute the type variable α with the input type τ₂. Note that this means that conceptually, the typechecker is creating all of the different (monomorphic) length versions, but we don’t need all of them for execution — having checked the types, we can have a single length function which would be similar to the function that Racket uses (i.e., the same “low level” code with types erased).

To see how this works, consider our length use, which has a type of ∀α. List〈α〉 -> Num. We get the following proof that ends in the exact type of length (remember that when you prove you climb up):

Γ ⊢ length : ∀α. List〈α〉 -> Num
——————————————————————————————————————————————
Γ ⊢ length〈Bool〉 : (List〈α〉 -> Num)[Bool/α]
——————————————————————————————————————————————
Γ ⊢ length〈Bool〉 : List〈Bool〉 -> Num    [...]
——————————————————————————————————————————————
Γ ⊢ {call length〈Bool〉 {cons〈Bool〉 ...}} : Num

The second rule for type abstractions is:

  Γ[α] ⊢ E : τ
———————————————————
Γ ⊢ 〈Λ〈α〉 E〉 : ∀α.τ

This rule means that to typecheck a type abstraction, we need to check the body while binding the type variable α — but it’s not bound to some specific type. Instead, it’s left unspecified (or non-deterministic) — and typechecking is expected to succeed without requiring an actual type. If some specific type is actually required, then typechecking should fail. The intuition behind this is that a polymorphic function can be one only if it doesn’t need some specific type — for example, {fun {x} {- {+ x 1} 1}} is an identity function, but it’s an identity that requires the input to be a number, and therefore it cannot have a polymorphic ∀α.α type like {fun {x} x}.

Another example is our length function — the actual type that the list holds better not matter, or our length function is not really polymorphic. This makes sense: to typecheck the function, this rule means that we need to typecheck the body, with α being some unknown type that cannot be used.

One thing that we need to be careful when applying any kind of abstraction (and the first rule does just that for a very simple lambda-calculus-like language) is infinite loops. But in the case of our type language, it turns out that this lambda-calculus that gets used at the meta-level is one of the strongly normalizing kinds, therefore no infinite loops happen. Intuitively, this means that we should be able to do this elaboration in just one pass over the code. Furthermore, there are no side-effects, therefore we can safely cache the results of applying type abstraction to speed things up. In the case of length, using it on a list of Num will lead to one such application, but when we later get to the recursive call we can reuse the (cached) first result.

Explicit polymorphism conclusionsThursday, November 29th

Quoted directly from the book:

Explicit polymorphism seems extremely unwieldy: why would anyone want to program with it? There are two possible reasons. The first is that it’s the only mechanism that the language designer gives for introducing parameterized types, which aid in code reuse. The second is that the language includes some additional machinery so you don’t have to write all the types every time. In fact, C++ introduces a little of both (though much more of the former), so programmers are, in effect, manually programming with explicit polymorphism virtually every time they use the STL (Standard Template Library). Similarly, the Java 1.5 and C# languages support explicit polymorphism. But we can possibly also do better than foist this notational overhead on the programmer.

Web ProgrammingTuesday, December 4th

PLAI §15

Consider web programming as a demonstration of a frequent problem. The HTTP protocol is stateless: each HTTP query can be thought of as running a program (or a function), getting a result, then killing it. This makes interactive applications hard to write.

For example, consider this behavior (which is based on a real story of a probably not-so-real bug known as “the ITA bug”):

Obviously there is some fundamental problem here — especially given that this problem plagued many websites early on (and these days these kind of problems can still be found in some places (like the registrar’s system), except that people are much more aware of it, and are much more prepared to deal with it). In an attempt to clarify what it is exactly that went wrong, we might require that each interaction will result in something that is deterministically based on what the browser window shows when the interaction is made — but even that is not always true. Consider the same scenario except with a bookstore and an “add to my cart” button. In this case you want to be able to add one item to the cart in the first window, then switch to the second window and click “add” there too: you want to end up with a cart that has both items.

The basic problem here is HTTP’s statelessness, something that both web servers and web browsers use extensively. Browsers give you navigation buttons and sometimes will not even communicate with the web server when you use them (instead, they’ll show you cached pages), they give you the ability to open multiple windows or tabs from the current one, and they allow you to “clone” the current tab. If you view each set of HTTP queries as a session — this means that web browsers allow you to go back and forth in time, explore multiple futures in parallel, and clone your current world.

These are features that the HTTP protocol intentionally allows by being stateless, and that people have learned to use effectively. A stateful protocol (like ssh, or ftp) will run in a single process (or a program, or a function) that is interacting with you directly, and this process dies only when you disconnect. A big advantage of stateful protocols is their ability to be very interactive and rely on state (eg, an editor updates a character on the screen, relying on the rest of it showing the same text); but stateless protocols can scale up better, and deal with a more hectic kind of interaction (eg, open a page on an online store, keep it open and buy the item a month later; or any of the above “time manipulation” devices).

Side-note: Some people think that Ajax is the answer to all of these problems. In reality, Ajax is layered on top of (asynchronous) web queries, so in fact it is the exact same situation. You do have an option of creating an application that works completely on the client side, but that wouldn’t be as attractive — and even if you do so, you’re still working inside a browser that can play the same time tricks.

Basic web programmingTuesday, December 4th

PLAI §16

Obviously, writing programs to run on a web server is a profitable activity, and therefore highly desirable. But when we do so, we need to somehow cope with the web’s statelessness. To see the implications from a PL point of view we’ll use a small “toy” example that demonstrates the basic issues — an “addition” service:

[Such a small application is not realistic, of course: you can obviously ask for both numbers on the same page. We still use it, though, to minimize the general interaction problem to a more comprehensible core problem.]

Starting from just that, consider how you’d want to write the code for such a service. (If you have experience writing web apps, then try to forget all of that now, and focus on just this basic problem.)

(web-display
  (+ (web-read "First number")
    (web-read "Second number")))

But this is never going to work. The interaction is limited to presenting the user with some data and that’s all — you cannot do any kind of interactive querying. For the purpose of making this more concrete, imagine that web-read and web-display both communicate information to the user via something like error: the information is sent and at the same time the whole computation is aborted. With this, the above code will just manage to ask for the first number and nothing else happens.

We therefore must turn this server function into three separate functions: one that shows the prompt for the first number, one that gets the value entered and shows the second prompt, and a third that shows the results page. The first two of these functions would send the information (and the respective computation dies) to the browser, including a form submission URL that will invoke the next function.

Assuming a generic “query argument” that represents the browser request, and a return value that represents a page for the browser to render, we have:

(define (f1 query)
  ... show the first question ...)

(define (f2 query)
  ... extract the number from the query ...
  ... show the second question ...)

(define (f3 query)
  ... extract the number from the query ...
  ... show the sum ...)

Note that f2 receives the first number directly, but f3 doesn’t. Yet, it is obviously needed to show the sum. A typical hack to get around this is to use a “hidden field” in the HTML form that f2 generates, where that field holds the second result. To make things more concrete, we’ll use some imaginary web API functions:

(define (f1 query)
  (web-read "First number" 'n1 "f2"))

(define (f2 query)
  (let ([n1 (get-field query 'n1)])
    ;; imagine that the following "configures" what web-read
    ;; produces by adding a hidden field to display
    (with-hidden-field 'n1 n1
      (web-read "Second number" 'n2 "f3"))))

(define (f3 query)
  (web-display
    "Your two numbers sum up to: "
    (+ (get-field query 'n1)
      (get-field query 'n2))))

Which would (supposedly) result in something like the following html forms when the user enters 1 and 2:

http://.../f1
<form action="http://.../f2">
  First number:
  <input type="text" name="n1" />
</form>

http://.../f2
<form action="http://.../f3">
  <input type="hidden" name="n1" value="1" />
  Second number:
  <input type="text" name="n2" />
</form>

http://.../f3
<form>
  <input type="text" name="result" value="3" readonly />
</form>

This is often a bad solution: it gets very difficult to manage with real services where the “state” of the server consists of much more than just a single number — and it might even include values that are not expressible as part of the form (for example an open database connection or a running process). Worse, the state is all saved in the client browser — if it dies, then the interaction is gone. (Imagine doing your taxes, and praying that the browser won’t crash a third time.)

Another common approach is to store the state information on the server, and use a small handle (eg, in a cookie) to identify the state, then each function can use the cookie to retrieve the current state of the service — but this is exactly how we get to the above bugs. It will fail with any of the mentioned time-manipulation features.

Continuations: Web ProgrammingTuesday, December 4th

To try and get a better solution, we’ll re-start with the original expression:

(web-display (+ (web-read "First number")
                (web-read "Second number")))

and assuming that web-read works as a regular function, we need to begin with executing the first read:

                (web-read "First number")

We then need to take that result and plug it into an expression that will read the second number and sum the results — that’s the same as the first expression, except that instead of the first web-read we use a “hole”:

(web-display (+ <*>
                (web-read "Second number")))

where <*> marks the point where we need to plug the result of the first question into. A better way to explain this hole is to make the expression into a function:

(lambda (<*>)
  (web-display (+ <*>
                  (web-read "Second number"))))

We can split the second and third interactions in the same way. First we can assemble the above two bits of code into an expression that has the same meaning:

((lambda (<*>)
  (web-display (+ <*> (web-read "Second number"))))
(web-read "First number"))

And now we can continue doing this and split the body of the consumer:

  (web-display (+ <*> (web-read "Second number")))

into a “reader” and the rest of the computation (using a new hole):

                      (web-read "Second number")  ; reader part

  (web-display (+ <*> <*2>))                      ; rest of comp

Doing all of this gives us:

((lambda (<*1>)
  ((lambda (<*2>)
      (web-display (+ <*1> <*2>)))
    (web-read "Second number")))
(web-read "First number"))

And now we can proceed to the main trick. Conceptually, we’d like to think about web-read as something that is implemented in a simple way:

(define (web-read prompt)
  (printf "~a: " prompt)
  (read-number))

except that the “real” thing would throw an error and die once the prompt is printed. The trick is one that we’ve already seen: we can turn the code inside-out by making the above “hole functions” be an argument to the reading function — a consumer callback for what needs to be done once the number is read. This callback is called a continuation, and we’ll use a /k suffix for names of functions that expect a continuation (k is a common name for a continuation argument):

(define (web-read/k prompt k)
  (printf "~a: " prompt)
  (k (read-number)))

This is not too different from the previous version — the only difference is that we make the function take a consumer function as an input, and hand it what we read instead of just returning it. It makes things a little easier, since we pass the hole function to web-read/k, and it will invoke it when needed:

(web-read/k "First number"
  (lambda (<*1>)
    (web-read/k "Second number"
      (lambda (<*2>)
        (web-display (+ <*1> <*2>))))))

You might notice that this looks too complicated; we could get exactly the same result with:

(web-display (+ (web-read/k "First number"
                            (lambda (<*>) <*>))
                (web-read/k "Second number"
                            (lambda (<*>) <*>))))

but then there’s not much point to having web-read/k at all… So why have it? Remember that the main problem is that in the context of a web server we think of web-read as something that throws an error and kills the computation. So if we use such a web-read/k with a continuation, we can make it save this continuation in some global state, so it can be used later when there is a value.

Simulating web readingTuesday, December 4th

We can now actually try all of this in plain Racket by simulating web interactions. This is useful to look at the core problem while avoiding the whole web mess that is uninteresting for the purpose of our discussion. The main feature that we need to emulate is statelessness — and as we’ve discussed, we can simulate that using error to guarantee that the process is properly killed for each interaction. We will do this in web-display which simulates sending the results to the client and therefore terminates the server process:

(define (web-display n)
  (error 'web-display "~s" n))

More importantly, we need to do it in web-read/k — but in this case, we need more than just an error — we need a way to store the k so the computation can be resumed later. To continue with the web analogy we do this in two steps: error is used to display the information (the input prompt), and the user action of entering a number and submitting it will be simulated by calling a function. Since the computation is killed after we show the prompt, the way to implement this is by making the user call a toplevel submit function — and before throwing the interaction error, we’ll save the k continuation in a global box:

(define (web-read/k prompt k)
  (set-box! resumer k)
  (error 'web-read
        "enter (submit N) to continue the following\n  ~a:"
        prompt))

submit uses the saved continuation:

(define (submit n)
  ((unbox resumer) n))

For safety, we’ll initialize resumer with a function that throws an error (a real one, not intended for interactions), make web-display reset it to the same function, and also make submit do so after grabbing its value — meaning that submit can only be used after a web-read/k. And for convenience, we’ll use raise-user-error instead of error, which is a Racket function that throws an error without a stack trace (since our errors are intended). It’s also helpful to disable debugging in DrRacket, so it won’t take us back to the code over and over again.

;; Fake web interaction library (to be used with manual code CPS-ing
;; examples)

#lang racket

(define error raise-user-error)

(define (nothing-to-do ignored)
  (error 'REAL-ERROR "No computation to resume."))

(define resumer (box nothing-to-do))

(define (web-display n)
  (set-box! resumer nothing-to-do)
  (error 'web-display "~s" n))

(define (web-read/k prompt k)
  (set-box! resumer k)
  (error 'web-read
        "enter (submit N) to continue the following\n  ~a:"
        prompt))

(define (submit n)
  ;; to avoid mistakes, we clear out `resumer' before invoking it
  (let ([k (unbox resumer)])
    (set-box! resumer nothing-to-do)
    (k n)))

We can now try out our code for the addition server, using plain argument names instead of <*>s:

(web-read/k "First number"
  (lambda (n1)
    (web-read/k "Second number"
      (lambda (n2)
        (web-display (+ n1 n2))))))

and see how everything works. You can also try now the bogus expression that we mentioned:

(web-display (+ (web-read/k "First number" (lambda (n) n))
                (web-read/k "Second number" (lambda (n) n))))

and see how it breaks: the first web-read/k saves the identity function as the global resumer, losing the rest of the computation.


Again, this should be familiar: we’ve taken a simple compound expression and “linearized” it as a sequence of an input operation and a continuation receiver for its result. This is essentially the same thing that we used for dealing with inputs in the lazy language — and the similarity is not a coincidence. The problem that we faced there was very different (representing IO as values that describe it), but it originates from a similar situation — some computation goes on (in whatever way the lazy language decides to evaluate it), and when we have a need to read something we must return a description of this read that contains “the rest of the computation” to the eager part of the interpreter that executes the IO. Once we get the user input, we send it to this computation remainder, which can return another read request, and so on.

Based on this intuition, we can guess that this can work for any piece of code, and that we can even come up with a nicer “flat” syntax for it. For example, here is a simple macro that flattens a sequence of reads and a final display:

(define-syntax web-code
  (syntax-rules (read display)
    [(_ (read n prompt) more ...)
    (web-read/k prompt
      (lambda (n)
        (web-code more ...)))]
    [(_ (display last))
    (web-display last)]))

and using it:

(web-code (read x "First number")
          (read y "Second number")
          (display (+ x y)))

However, we’ll avoid such cuteness to make the transformation more explicit for the sake of the discussion. Eventually, we’ll see how things can become even better than that (as done in Racket): we can get to write plain-looking Racket expressions and avoid even the need for an imperative form for the code. In fact, it’s easy to write this addition server using Racket’s web server framework, and the core of the code looks very simple:

(define (start initial-request)
  (page "The sum is: "
        (+ (web-read "First number")
          (web-read "Second number"))))

There is not much more than that — it has two utilities, page creates a well-formed web page, and web-read performs the reading. The main piece of magic there is in send/suspend which makes the web server capture the computation’s continuation and store it in a hash table, to be retrieved when the user visits the given URL. Here’s the full code:

#lang web-server/insta
(define (page . body)
  (response/xexpr
  `(html (body ,@(map (lambda (x)
                        (if (number? x) (format "~a" x) x))
                      body)))))
(define (web-read prompt)
  ((compose string->number (curry extract-binding/single 'n)
            request-bindings send/suspend)
  (lambda (k)
    (page `(form ([action ,k])
              ,prompt ": " (input ([type "text"] [name "n"])))))))
(define (start initial-request)
  (page "The sum is: "
        (+ (web-read "First number")
          (web-read "Second number"))))

More Web TransformationsTuesday, December 4th

PLAI §17

Transforming a recursive functionTuesday, December 4th

We did the above transformation on a simple expression — and as you’d guess, it’s possible to make it work for recursive functions too, although it gets a little tricky. As done above, we start with some plain looking code:

(define (sum prompts)
  (if (null? prompts)
    0
    (+ (web-read (first prompts))
      (sum (rest prompts)))))

Further, we want this function to be usable as a library function — it should be useful for web applications that need this functionality. One result of this is that it doesn’t web-display its result.

We begin by converting the web-read to its continuation version:

(define (sum prompts)
  (if (null? prompts)
    0
    (web-read/k (first prompts)
      (lambda (n)
        (+ n
          (sum (rest prompts)))))))

But using web-read/k immediately terminates the running computation, so this won’t work. Another way to see the problem is that the continuation input to web-read/k should have the rest of the computation, yet in this version it only has the addition — if sum is used as in some larger context as a library function, then that whole context will be lost. The way to solve this is to make sum itself take a continuation, which we’ll get in a similar way — by rewriting it as a sum/k function:

(define (sum/k prompts k)
  (if (null? prompts)
    0
    (web-read/k (first prompts)
      (lambda (n)
        (+ n
          (sum (rest prompts)))))))

We also need to deal with the recursive sum call and change it to a sum/k. Clearly, the continuation is the same continuation that the original sum was called with, so we need to pass it on in the recursive call too:

(define (sum/k prompts k)
  (if (null? prompts)
    0
    (web-read/k (first prompts)
      ;; get the value provided by the user, and add it to the value
      ;; that the recursive call generates
      (lambda (n)
        (+ n
          (sum/k (rest prompts)
                  k))))))

But there is another problem now: the addition is done outside of the continuation, therefore it will be lost as soon as there’s a second web-read/k call. In other words, computation bits that are outside of any continuations are going to disappear, and therefore they must be encoded as an explicit part of the continuation. The solution is therefore to move the addition into the continuation:

(define (sum/k prompts k)
  (if (null? prompts)
    0
    (web-read/k (first prompts)
      (lambda (n)
        (sum/k (rest prompts)
              (lambda (sum-of-rest)
                (k (+ n sum-of-rest))))))))

Note that with this code every new continuation is bigger — it contains the previous continuation (note that “contains” here is done by making it part of the closure), and it also contains one new addition.

But if the continuation is only getting bigger, then how do we ever get a result out of this? Put differently, when we reach the end of the prompt list, what do we do? — Clearly, we just return 0, but that silently drops the continuation that we worked so hard to accumulate. This means that just returning 0 is wrong — instead, we should send the 0 to the pending continuation:

(define (sum/k prompts k)
  (if (null? prompts)
    (k 0)
    (web-read/k (first prompts)
      (lambda (n)
        (sum/k (rest prompts)
              (lambda (sum-of-rest)
                (k (+ n sum-of-rest))))))))

This makes sense now: this sum/k is a utility to be used in a web server application, and such applications need to be transformed in a similar way to what we’re doing. Therefore, our own sum/k is a function that expects to be invoked from such transformed code — so it needs to have an argument for the waiting receiver, and it needs to pass that receiver around (accumulating more functionality into it) until it’s done.

To try it, we need a top-level consumer value to pass on to the sum/k call. The obvious choice in this case is to use web-display:

(sum/k '("First" "Second" "Third")
      (lambda (sum) (web-display sum)))

or, more simply:

(sum/k '("First" "Second" "Third")
      web-display)

Using sum/kTuesday, December 4th

To get some more experience with this transformation, we’ll try to convert some code that uses the above sum/k. For example, lets add a multiplier argument that will get multiplied by the sum of the given numbers. Begin with the simple code. This is an actual application, so we’re writing just an expression to do the computation and show the result, not a function.

(web-display (* (web-read "Multiplier")
                (sum '("First" "Second" "Third"))))

We now need to turn the two function calls into their */k form. Since we covered sum/k just now, begin with that. The first step is to inspect its continuation: this is the same code after we replace the sum call with a hole:

(web-display (* (web-read "Multiplier")
                <*>))

Now take this expression, make it into a function by abstracting over the hole and call it n, and pass that to sum/k:

(sum/k '("First" "Second" "Third")
      (lambda (n)
        (web-display (* (web-read "Multiplier")
                        n))))

(Note that this is getting rather mechanical now.) Now for the web-read part, we need to identify its continuation — that’s the expression that surrounds it inside the first continuation function, and we’ll use m for the new hole:

        (* m
            n)

As above, abstract over m to get a continuation, and pass it into web-read/k:

(sum/k '("First" "Second" "Third")
      (lambda (n)
        (web-read/k "Multiplier"
                    (lambda (m)
                      (web-display (* m n))))))

and we’re done. An interesting question here is what would happen if instead of the above, we start with the web-read and then get to the sum? We’d end up with a different version:

(web-read/k "Multiplier"
            (lambda (m)
              (sum/k '("First" "Second" "Third")
                    (lambda (n)
                      (web-display (* m n))))))

Note how these options differ — one reads the multiplier first, and the other reads it last.

Side-note: if in the last step of turning web-read to web-read/k we consider the whole expression when we formulate the continuation, then we get to the same code. But this isn’t really right, since it is converting code that is already-converted.

In other words, our conversion results in code that fixes a specific evaluation order for the original expression. The way that the inputs happen in the original expression

(web-display (* (web-read "Multiplier")
                (sum '("First" "Second" "Third"))))

is unspecified in the code — it only happens to be left-to-right implicitly, because Racket evaluates function arguments in that order. However, the converted code does not depend on how Racket evaluates function arguments. (Can you see a similar conclusion here about strictness?)

Note also another property of the converted code: every intermediate result has a name now. This makes sense, since another way to fix the evaluation order is to do just that. For example, convert the above to either

(let* ([m (web-read "Multiplier")]
      [n (sum '("First" "Second" "Third"))])
  (* m n))

or

(let* ([n (sum '("First" "Second" "Third"))]
      [m (web-read "Multiplier")])
  (* m n))

This is also a good way to see why this kind of conversion can be a useful tool in compiling code: the resulting code is in a kind of a low-level form that makes it easy to translate to assembly form, where function calls are eliminated, and instead there are only jumps (since all calls are tail-calls). In other words, the above can be seen as a piece of code that is close to something like:

val n = sum(["First","Second","Third"])
val m = web_read("Multiplier")
web_display(m*n)

and it’s almost visible in the original converted code if we format it in a very weird way:

;; sum(["First","Second","Third"]) -> n
(sum/k '("First" "Second" "Third") (lambda (n)
;; web_read("Multiplier") -> m
(web-read/k "Multiplier" (lambda (m)
;; web_display(m*n)
(web-display (* m n))))))

Converting stateful codeTuesday, December 4th

Another case to consider is applying this transformation to code that uses mutation with some state. For example, here’s some simple account code that keeps track of a balance state:

(define account
  (let ([balance (box 0)])
    (lambda ()
      (set-box! balance
                (+ (unbox balance)
                  (web-read (format "Balance: ~s; Change"
                                    (unbox balance)))))
      (account))))

(Note that there is no web-display here, since it’s an infinite loop.) As usual, the fact that this function is expected to be used by a web application means that it should receive a continuation:

(define account/k
  (let ([balance (box 0)])
    (lambda (k)
      (set-box! balance
                (+ (unbox balance)
                  (web-read (format "Balance: ~s; Change"
                                    (unbox balance)))))
      (account))))

Again, we need to convert the web-read into web-read/k by abstracting out its continuation. We’ll take the set-box! expression and create a continuation out of it:

      (set-box! balance
                (+ (unbox balance)
                  <*>))

and using change as the name for the continuation argument, we get:

(define account/k
  (let ([balance (box 0)])
    (lambda (k)
      (web-read/k (format "Balance: ~s; Change"
                          (unbox balance))
                  (lambda (change)
                    (set-box! balance (+ (unbox balance) change))))
      (account))))

And finally, we translate the loop call to pass along the same continuation it received (it seems suspicious, but there’s nothing else that could be used there):

(define account/k
  (let ([balance (box 0)])
    (lambda (k)
      (web-read/k (format "Balance: ~s; Change" (unbox balance))
                  (lambda (change)
                    (set-box! balance (+ (unbox balance) change))))
      (account/k k))))

But if we try to run this — (account/k web-display) — we don’t get any result at all: it reads one number and then just stops without the usual request to continue, and without showing any result. The lack of printed result is a hint for the problem — it must be the void return value of the set-box!. Again, we need to remember that invoking a web-read/k kills any pending computation and the following (resume) will restart its continuation — but the recursive call is not part of the loop.

The problem is the continuation that we formulated:

      (set-box! balance
                (+ (unbox balance)
                  change))

which should actually contain the recursive call too:

      (set-box! balance
                (+ (unbox balance)
                  change))
      (account/k k)

In other words, the recursive call was left outside of the continuation, and therefore it was lost when the fake server terminated the computation on a web-read/k — so it must move into the continuation as well:

(define account/k
  (let ([balance (box 0)])
    (lambda (k)
      (web-read/k (format "Balance: ~s; Change" (unbox balance))
                  (lambda (change)
                    (set-box! balance (+ (unbox balance) change))
                    (account/k k))))))

and the code now works. The only suspicious thing that we’re still left with is the loop that passes k unchanged — but this actually is the right thing to do here. The original loop had a tail-recursive call that didn’t pass along any new argument values, since the infinite loop is doing its job via mutations to the box and nothing else was done in the looping call. The continuation of the original call is therefore also the continuation of the second call, etc. All of these continuations are closing over a single box and this binding does not change (it cannot change if we don’t use a set!); instead, the boxed value is what changes through the loop.

Converting higher order functionsTuesday, December 4th

Next we try an even more challenging transformation: a higher order function. To get a chance to see more interesting examples, we’ll have some more code in this case.

For example, say that we want to compute the sum of squares of a list. First, the simple code (as above, there’s no need to wrap a web-display around the whole thing, just make it return the result):

(define (sum l) (foldl + 0 l))
(define (square n) (* n n))
(define (read-number prompt)
  (web-read (format "~a number" prompt)))
(web-display (sum (map (lambda (prompt)
                        (square (read-number prompt)))
                      '("First" "Second" "Third"))))

Again, we can begin with web-read — we want to convert it to the continuation version, which means that we need to convert read-number to get one too. This transformation is refreshingly trivial:

(define (read-number/k prompt k)
  (web-read/k (format "~a number" prompt) k))

This is an interesting point — it’s a simple definition that just passes k on, as is. The reason for this is similar to the simple continuation passing of the imperative loop: the pre-translation read-number is doing a simple tail call to web-read, so the evaluation context of the two is identical. The only difference is the prompt argument, and that’s the same format call.

Of course things would be different if format itself required a web interaction, since then we’d need some format/k, but without that things are really simple. The same goes for the two utility functions — sum and square: they’re not performing any web interaction so it seems likely that they’ll stay the same.

We now get to the main expression, which should obviously change since it needs to call read-number/k, so it needs to send it some continuation. By now, it should be clear that passing an identity function as a continuation is going to break the surrounding context once the running computation is killed for the web interaction. We need to somehow generate a top-level identity continuation and propagate it inside, and the sum call should be in that continuation together with the web-display call. Actually, if we do the usual thing and write the expression with a <*> hole, we get:

(web-display (sum (map (lambda (prompt) (square <*>))
                      '("First" "Second" "Third"))))

and continuing with the mechanical transformation that we know, we need to abstract over this expression+hole into a function, then pass it as an argument to read-number/k:

;; very broken
(read-number/k
(lambda (<*>)
  (web-display (sum (map (lambda (prompt) (square <*>))
                          '("First" "Second" "Third"))))))

But that can’t work in this case — we need to send read-number/k a prompt, but we can’t get a specific one since there is a list of them. In fact, this is related to a more serious problem — pulling out read-number/k like this is obviously broken since it means that it gets called only once, instead, we need to call it once for each prompt value.

The solution in this case is to convert map too:

(web-display (sum (map/k (lambda (prompt)
                          (square (read-number prompt)))
                        '("First" "Second" "Third")
                        ...some-continuation...)))

and of course we should move web-display and sum into that continuation:

(map/k (lambda (prompt) (square (read-number prompt)))
      '("First" "Second" "Third")
      (lambda (l) (web-display (sum l))))

We can now use read-number/k, but the question is what should it get for it’s continuation?

(map/k (lambda (prompt) (square (read-number/k prompt ???)))
      '("First" "Second" "Third")
      (lambda (l) (web-display (sum l))))

Clearly, map/k will need to somehow communicate some continuation to the mapped function, which in turn will send it to read-number/k. This means that the mapped function should get converted too, and gain a k argument. To do this, we’ll first make things convenient and have a name for it (this is only for convenience, we could just as well convert the lambda directly):

(define (read-squared prompt)
  (square (read-number/k prompt ???)))
(map/k read-squared
      '("First" "Second" "Third")
      (lambda (l) (web-display (sum l))))

Then convert it in the now-obvious way:

(define (read-squared/k prompt k)
  (read-number/k prompt
                (lambda (n)
                  (k (square n)))))
(map/k read-squared/k
      '("First" "Second" "Third")
      (lambda (l) (web-display (sum l))))

Everything is in place now — except for map/k, of course. We’ll start with the definition of plain map:

(define (map f l)
  (if (null? l)
    null
    (cons (f (first l)) (map f (rest l)))))

The first thing in turning it into a map/k is adding a k input,

(define (map f l k)
  (if (null? l)
    null
    (cons (f (first l)) (map f (rest l)))))

and now we need to face the fact that the f input is itself one with a continuation — an f/k:

(define (map/k f/k l k)
  (if (null? l)
    null
    (cons (f (first l)) (map f (rest l)))))

Consider now the single f call — that should turn into a call to f/k with some continuation:

(define (map/k f/k l k)
  (if (null? l)
    null
    (cons (f/k (first l) ???) (map f (rest l)))))

but since f/k will involve a web interaction, it will lead to killing the cons around it. The solution is to move that cons into the continuation that is handed to f/k — and as usual, this involves the second cons argument — the continuation is derived from replacing the f/k call by a hole:

    (cons <*> (map f (rest l)))

and abstracting that hole, we get:

(define (map/k f/k l k)
  (if (null? l)
    null
    (f/k (first l)
        (lambda (result)
          (cons result (map f (rest l)))))))

We now do exactly the same for the recursive map call — it should use map/k with f/k and some continuation:

(define (map/k f/k l k)
  (if (null? l)
    null
    (f/k (first l)
        (lambda (result)
          (cons result (map/k f/k (rest l) ???))))))

and we need to move the surrounding cons yet again into this continuation. The holed expression is:

          (cons result <*>)

and abstracting that and moving it into the map/k continuation we get:

(define (map/k f/k l k)
  (if (null? l)
    null
    (f/k (first l)
        (lambda (result)
          (map/k f/k (rest l)
                  (lambda (new-rest)
                    (cons result new-rest)))))))

There are just one more problem with this — the k argument is never used. This implies two changes, since it needs to be used once in each of the conditional branches. Can you see where it should be added? (Try to do this before reading the code below.)

The complete code follows:

(define (map/k f/k l k)
  (if (null? l)
    (k null)
    (f/k (first l)
        (lambda (result)
          (map/k f/k (rest l)
                  (lambda (new-rest)
                    (k (cons result new-rest))))))))
(define (sum l) (foldl + 0 l))
(define (square n) (* n n))
(define (read-number/k prompt k)
  (web-read/k (format "~a number" prompt) k))
(define (read-squared/k prompt k)
  (read-number/k prompt (lambda (n) (k (square n)))))
(map/k read-squared/k
      '("First" "Second" "Third")
      (lambda (l) (web-display (sum l))))

Highlevel Overview on ContinuationsTuesday, December 4th

Very roughly speaking, the transformation we made turns a function call like

(...stuff... (f ...args...) ...more-stuff...)

into

(f/k ...args...
    (lambda (<*>)
      (...stuff... <*> ...more-stuff...)))

This is the essence of the solution to the statelessness problem: to remember where we left off, we conveniently flip the expression inside-out so that its context is all stored in its continuation. One thing to note is that we did this only for functions that had some kind of web interaction, either directly or indirectly (since in the indirect case they still need to carry around the continuation).

If we wanted to make this process a completely mechanical one, then we wouldn’t have been able to make this distinction. After all, a function like map is perfectly fine as it is, unless it happens to be used with a continuation-carrying function — and that’s something that we know only at runtime. We would therefore need to transform all function calls as above, which in turn means that all functions would need to get an extra continuation argument.

Here are a few things to note about such fully-transformed code: