Does Pharo provide tail-call optimisation?

Question

The implementation of Integer>>#factorial in Pharo is:

factorial
        "Answer the factorial of the receiver."

        self = 0 ifTrue: [^ 1].
        self > 0 ifTrue: [^ self * (self - 1) factorial].
        self error: 'Not valid for negative integers'

This a tail-recursive definition. However, I can evaluate 10000 factorial without error in the workspace.

Does Pharo perform tail-call optimisation in any circumstances, is it doing some other optimisation, or is it just using a really deep stack?

Answer 1

There is no mystery in the execution model of Pharo. The recursive fragment

^ self * (self - 1) factorial

that happens inside the second ifTrue: compiles to the following sequence of bytecodes:

39 <70> self                  ; receiver of outer message *
40 <70> self                  ; receiver of inner message -
41 <76> pushConstant: 1       ; argument of self - 1
42 <B1> send: -               ; subtract
43 <D0> send: factorial       ; send factorial (nothing special here!) 
44 <B8> send: *               ; multiply
45 <7C> returnTop             ; return

Note that in line 43 nothing special happens. The code just sends factorial in the same way it would, had the selector been any other. In particular we can see that there is no special manipulation of the stack here.

This doesn't mean that there cannot be optimizations in the underlying native code. But that is a different discussion. It is the execution model the one that matters to the programmer because any optimization underneath bytecodes is meant to support this model at the conceptual level.

UPDATE

Interestingly, the non-recursive version

factorial2
  | f |
  f := 1.
  2 to: self do: [:i | f := f * i].
  ^f

is a little bit slower that the recursive one (Pharo). The reason must be that the overhead associated to increasing i is a little bit greater than the recursive send mechanism.

Here are the expressions I tried:

[25000 factorial] timeToRun
[25000 factorial2] timeToRun