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The evolution of an OCaml programmer

Christophe Deleuze

May 23, 2008

Abstract: A few ways to describe the computation of (should I just say “program”?) the factorial function in OCaml. We begin with the classical for loop and recursion and end with Church naturals in the lambda calculus. On the way, we meet tail, structural, and open recursion, streams and point-free style, Peano, functors, continuation passing style (CPS), meta-programming, call/cc, trampolined style, reactive programming, and linear logic (not necessarily in this order, though). Inspiration came from [12], itself inspired by [2].

We start with one of the most straightforward programs for the factorial function: as a recursive procedure, generating a linear recursive process [1].

  let rec fact n = 
    if n = 0 then 1
    else n * fact (n-1)

But then we realize that OCaml also has imperative features, so we can eliminate these costly recursive calls! Here’s an imperative procedure generating a linear iterative process.

  let fact n =
    let a = ref 1 in
    for i = 1 to n do a := !a * i done;

Hey, this imperative stuff is ugly, didn’t you know that tail recursion can be as efficient as a loop? Here’s a recursive procedure generating a linear iterative process.

  let fact n =
    let rec f i a = if i = n then a else f (i+1) ((i+1)*a)
    f 0 1

The next, rather stupid, implementation could arguably be described as a linear recursive process generated by an iterative procedure. Rant: OCaml arrays have their first element at position 0, which is often inconvenient (remember Pascal arrays?)

  let fact n =
    let a = Array.make (n+1) 1
    for i = 2 to n do
      a.(i) <- a.(i-1) * i

We’ve been using syntactic sugar for function declarations, let’s avoid this and make the lambda explicit:

  let fact =
    let rec f i n a = if i = n then a else f (i+1) n ((i+1)*a)
    function n -> f 0 n 1

or alternatively:

  let fact = function n ->
    let rec f i a = if i = n then a else f (i+1) ((i+1)*a)
    f 0 1

Feeling lispy? Turn these infix operators into prefix functions (requires even more parentheses than in Lisp!):

  let fact = function n ->
    let rec f i a = if i = n then a else f ((+) i 1) ( ( * ) ((+) i 1) a)
    f 0 1

This “if then else” expression is too Pascalish, it doesn’t look mathematical enough; let’s being more declarative by using a transformational style:

  let rec fact = function
    | 0 -> 1
    | n -> n * fact (n-1)

Oops! We forgot to use tail recursion!

  let fact n =
    let rec f n a = match n with
    | 0 -> a
    | n -> f (n-1) (a*n)
    f n 1

General recursion is not the only way to go. Recursion operators can be fun(ctional) too. Did you know you could do so many things with fold? [8]

  let rec list_from_to n m =
    if n > m then [] else n :: (list_from_to (n+1) m)

  let fact = fun n -> List.fold_right (fun n acc -> acc*n) (list_from_to 1 n) 1

But again, neither list_from_to nor fold_right are tail-recursive.

  let list_from_to n m =
    let rec mkl l m =
      if n > m then l else mkl (m::l) (m-1)
    mkl [] m

  let fact = fun n -> List.fold_left (fun acc n -> acc*n) 1 (list_from_to 1 n)

That’s good but hey, how useful is tail recursion if this list_from_to stuff uses linear space? Lazy lists (aka streams) allow us to do the same thing in constant space with the very same formulation. Look:

  let stream_from_to n m = 
    let f i = if (n+i) <= m then Some (n+i) else None
    Stream.from f

  let stream_fold f i s =
    let rec help acc =
        let n = Stream.next s in
        help (f acc n)
      with Stream.Failure -> acc
    help i

  let fact = fun n -> stream_fold (fun acc n -> acc*n) 1 (stream_from_to 1 n)

If you read Backus’ paper about FP [3], you’d probably prefer to write it in point-free style1:

  let insert unit op seq =
      (fun acc n -> op acc n)

  let iota = stream_from_to 1

  let fact = 
    let (/) = insert
    and ( @ ) f g x = f(g x)  (* sadly, we can’t use ’o’ as infix symbol *)
    ((/) 1 ( * )) @ iota

We could define the stream insert with recursion rather than using the fold operator:

  let insert unit op seq =
    let rec help acc =
        let n = Stream.next seq in
        help (op acc n)
      with Stream.Failure -> acc
    help unit 

If we don’t like OCaml built-in Stream module, it’s easy to define streams with state-full functions. Rather than raising an exception at stream end, we’ll use an option type for its value.

  let stream_from_to n =
    let current = ref (n-1)
    fun m () -> if !current < m then begin
      incr current;
      Some !current
    end else None

  let stream_fold f i st =
    let rec help acc =
      match st () with
        Some n -> help (f acc n)
      | None -> acc
    help i

  let fact n = stream_fold ( * ) 1 (stream_from_to 1 n)

Open recursion allows many nice things like tracing calls or extending types [11, 7].

  let ofact f n =
    if n = 0 then 1
    else n * f (n-1)
  let rec fact n = ofact fact n

Or alternatively

  let rec fix f x = f (fix f) x
  let fact = fix ofact

Repeat: “I should use tail recursion”...

  let ofact f acc n =
    if n = 0 then acc
    else f (n*acc) (n-1)
  let fact n =
    let rec help a n = ofact help a n
    help 1 n

All these functions make use of the quite limited CPU based int type. OCaml provides exact integer arithmetic through the Big_int module:

  open Big_int

  let rec fact = function
      0 -> zero_big_int
    | n -> mult_big_int (big_int_of_int n) (fact (n-1))

Another way to get rid of this int data type is to build natural numbers from scratch, as defined, for example, by Peano. In the process we switch from general to structural recursion (thus syntactically ensuring termination and making our function total) :

  type nat = Zero | Succ of nat

  let rec (+) n m =
    match n with
    | Zero    -> m
    | Succ(p) -> p + (Succ m)
  let rec ( * ) n m =
    match n with
    | Zero       -> Zero
    | Succ(Zero) -> m
    | Succ(p)    -> m + (p * m)

  let rec fact n =
    match n with
    | Zero    -> Succ(Zero)
    | Succ(p) -> n * (fact p)
  (* convenience functions *)

  let rec int_of_peano = function
      Zero    -> 0
    | Succ(p) -> succ (int_of_peano p)
  let rec peano_of_int = function
      0 -> Zero
    | n -> Succ(peano_of_int (n-1))

Tail-recursive versions are left as (easy) exercises to the reader!

What about using functors? Whatever representation we use for naturals, they can be defined as a module with the NATSIG signature defined below. Then, a functor taking a module of NATSIG signature can be defined to provide a factorial function for any NATSIG datatype.

  module type NATSIG = 
      type t 
      val zero:t
      val unit:t
      val mul:t->t->t
      val pred:t->t

  module FactFunct(Nat:NATSIG) = 
      let rec fact n:Nat.t = 
        if n = Nat.zero then Nat.unit else Nat.mul n (fact (Nat.pred n))

Here are examples of uses with native integers, Peano naturals and OCaml big_ints:

  module NativeIntNats =
      type t = int
      let zero = 0
      let unit = 1
      let mul = ( * )
      let pred n = n-1

  module PeanoNats =
      type t = Zero | Succ of t
      let zero = Zero
      let unit = Succ(Zero)

      let rec add n m =
        match n with
        | Zero    -> m
        | Succ(p) -> add p (Succ m)
      let rec mul n m =
        match n with
        | Zero       -> Zero
        | Succ(Zero) -> m
        | Succ(p)    -> add m (mul p m)

      let pred = function Succ(n) -> n | Zero -> Zero

  module BigIntNats =
      type t = Big_int.big_int
      let zero = Big_int.zero_big_int
      let unit = Big_int.unit_big_int
      let pred = Big_int.pred_big_int
      let mul =  Big_int.mult_big_int

  module NativeFact = FactFunct(NativeIntNats)
  module PeanoFact = FactFunct(PeanoNats)
  module BigIntFact = FactFunct(BigIntNats)

In the previous examples, to make the function tail-recursive we used a second accumulator parameter, which in some sense remembered the past computations (actually just their result).

Another way to turn a recursive function into a tail-recursive one is to use continuation passing style (aka CPS)2. The series of recursive calls actually build as a function the sequence of computations to be done, that will all be performed on the final base call (for n=0).

This could be considered cheating since, although the function is tail-recursive, the size of the “accumulator” grows linearly with the number of recursive calls...

  let fact =
    let rec f n k =
      if n=0 then k 1
      else f (n-1) (fun r -> k (r*n))
    function n -> f n (fun x -> x)

This is not so different from using meta-programming. Metaocaml [15] is a nice meta-programming extension of OCaml. Using that, you can write a function that takes an integer n as parameter and produces the code that, when run, will compute the factorial of n... (just for fun)

  let rec gfact = function
    | 0 -> .<1>.
    | n -> .< n * .~(gfact (n-1)) >.
  let fact n = .! gfact n

Of course, this can be made tail-recursive too! Then it looks very similar to the previous example using continuations:

  let gfact n = 
    let rec f n acc =
      if n=0 then acc
      else f (n-1) .< n * .~acc>.
    in f n .<1>.

Using first class continuations, we can run our function step by step as a synchronous process possibly among other processes [5].3

  open Callcc

  type ’a process = Proc of (’a -> ’a) | Cont of ’a cont

  (* Primitives for the process queue.  Exit continuation will always be first *)

  let enqueue, dequeue =
    let q = ref [] in
    (fun e -> q := !q @ [e]),
    (fun () -> match !q with
      e::f::l -> q := e::l; f     (* keep exit cont at head of queue *)
    | [e]     -> q := []; e)      (* no more process to run *)

  let run p =
    match p with
      Proc proc -> proc ()
    | Cont k -> throw k ()

  (* Queue back a suspending process, dequeue and run *)

  let swap_run p =
    enqueue p;
    run (dequeue ())

  (* Two functions to be used in processes.  halt to terminate,
     pause_handler to suspend *)

  let halt () = run (dequeue ())

  let pause_handler () = 
    callcc (fun k -> swap_run (Cont k))

  let create_process th =
    Proc (fun () -> th (); halt ())

  (* Dispatcher puts exit continuation in process queue, adds processes
     through init_q and runs first process. *)

  let dispatcher init_q =
      (fun exitk ->
        enqueue (Cont exitk);
        init_q ();
        halt ())

  (* Factorial as a process *)

  let fact_maker n =
      (fun () ->
        let rec fact n =
          if n=0 then 1
          else begin
            n * fact (n-1)
        in Printf.printf "fact=%i\n" (fact n))

  let fact n = dispatcher (fun () -> enqueue (fact_maker n));;

Trampolined style [6] is another way to run our function step by step concurrently with others, but without the need for first class continuations. Instead, we’ll use CPS. That implies that we must use a tail recursive version of factorial in this case.

  type ’a thread = Done of ’a | Doing of (unit -> ’a thread)

  let return v = Done v
  let bounce f = Doing f

  (* factorial function *)

  let rec fact_tramp i acc =
    if i=0 then
      return acc
      bounce (fun () -> fact_tramp (i-1) (acc*i))
  (* one thread scheduler *)

  let rec pogostick f =
    match f () with
    | Done v -> v
    | Doing f -> pogostick f

  (* give our fact trampoline function to the scheduler *)

  let fact n =
    pogostick (fun () -> fact_tramp n 1)

Functional reactive programming is still another way to describe concurrent, synchronous, computations. In reactiveML [10], a factorial computing process could be written as:

  let rec process fact n =
    if n<=1 then 1
      let v = run (fact (n-1)) in

In a linear logic based language [4], each bound name is required to be referenced exactly once. This may seem odd but ensures nice properties, e.g. avoiding the need for garbage collection. Pretending we have some “linear OCaml” compiler, we could write the factorial this way:

  let dup x = (x,x)   (* dup and kill would be    *)
  let kill x = ()     (* provided by linear OCaml *)

  let rec fact n =
    let n,n’ = dup n
    if n=0 then (kill n’; 1)
      let n,n’ = dup n’ in
      n’ * fact (n-1)

Computing with Peano numbers like we did previously is fun, but let’s be more functional and use Church naturals instead! Sadly, although they can be defined in OCaml, the type system rejects the pred operator. Never mind, let’s quickly build4 a lambda calculus interpreter!5

There may be a subtle bug in the way alpha conversion is performed. Can you find it?

  (* the type of lambda terms *)

  type lambda = Var of string | Abs of string * lambda | App of lambda * lambda

  (* free variables in t *)

  let rec fv t =
    match t with
    | Var x -> [ x ]
    | Abs(x,l) -> List.filter (fun e -> e<>x) (fv l)
    | App(t1,t2) -> fv t1 @ fv t2

  (* in t, rename olds present in seen – seen under lambdas *)

  let rec alpha olds seen nb t =
    match t with
    | Var s -> if List.mem s seen then Var (s^nb) else t
    | App(l1,l2) -> App(alpha olds seen nb l1, alpha olds seen nb l2)
    | Abs(s,l)   -> 
        if List.mem s olds then Abs(s^nb, alpha olds (s::seen) nb l) 
        else                    Abs(s, alpha olds seen nb l)
  (* body[arg/s], alpha conversion already done *)

  let rec ssubst body s arg =
    match body with
    | Var s’     -> if s=s’ then arg else Var s’
    | App(l1,l2) -> App(ssubst l1 s arg, ssubst l2 s arg)
    | Abs(o,l)   -> if o=s then body else Abs(o, ssubst l s arg)

  let gen_nb =
    let nb = ref 0 in function () -> incr nb; !nb

  (* body[arg/s], avoiding captures *)

  let subst body s arg =
    let fvs = fv arg in
    ssubst (alpha fvs [] (string_of_int (gen_nb())) body) s arg

  (* call by name evaluation *)

  let rec cbn t =
    match t with
    | Var _ -> t
    | Abs _ -> t
    | App(e1,e2) -> match cbn e1 with
      | Abs(x,e) -> cbn (subst e x e2)
      | e1’      -> App(e1’, e2)

  (* normal order evaluation *)

  let rec nor t =
    match t with
    | Var _ -> t
    | Abs(x,e) -> Abs(x,nor e)
    | App(e1,e2) -> match cbn e1 with
      | Abs(x,e) -> nor (subst e x e2)
      | e1’ -> let e1” = nor e1’ in
        App(e1”,nor e2)

  (* some useful basic constructs *)

  let succ = Abs("n", Abs("f", Abs("x",
                 App(Var"f", App(App(Var"n",Var"f"),Var"x")))))

  let pred = Abs("n",Abs("f",Abs("x",

  let mult = Abs("n",Abs("m",Abs("f",Abs("x",

  let zero = Abs("f",Abs("x",Var"x"))

  let t = Abs("x",Abs("y",Var"x"))
  let f = Abs("x",Abs("y",Var"y"))
  let iszero = Abs("n",App(App(Var"n",Abs("x",f)), t))

  let y = Abs("g", App(Abs("x", App(Var"g",App(Var"x",Var"x"))),
                       Abs("x", App(Var"g",App(Var"x",Var"x")))))

  (* now let’s build the factorial function *)

  let fact = 
    let ofact = Abs("f",Abs("n",
                                App(App(mult,Var "n"),
    in App(ofact,App(y,ofact))

  (* convenience functions *)

  let church_of_int n =
    let rec coi n = if n=0 then Var"x" else App(Var"f", coi (n-1))
    Abs("f",Abs("x", coi n))

  exception NotaNat

  let int_of_church n =
    let rec ioc n f x =
      match n with
        Var x’ -> if x=x’ then 0 else raise NotaNat
      | App(Var f’,r) -> if f=f’ then (ioc r f x) + 1 else raise NotaNat
      | _ -> raise NotaNat
    match n with
      Abs(f,Abs(x,r)) -> ioc r f x
    | _ -> raise NotaNat
  let fact n = int_of_church (nor (App(fact,church_of_int n)))

All right, that’s enough for today. Next time, we may talk about objects, syntax extensions, MVars and a few other nice things.


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FP’s insert operator is denoted ’/’ and the unit parameter is given by the unit functional form (takes a function as argument and returns its unit if there is one.)
Could someone provide me with a good reference for this?
Straight OCaml does not feature first class continuations but a toy extension for them exists [9]. A more robust library also supports delimited continuations [13].
I must admit it took me (much) more time than I first expected...
Code for cbn and nor is from [14].

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