http://www.cs.sfu.ca/CC/310/pwfong/Lisp/2/tutorial2.html

Recursive functions are usually easier to reason about. Notice how we articulate the correctness of recursive functions in this and the previous tutorial. However, some naive programmers complain that recursive functions are slow when compared to their iterative counter parts. For example, consider the original implementation of `factorial` we saw in the previous tutorial:

(defun factorial (N) "Compute the factorial of N." (if (= N 1) 1 (* N (factorial (- N 1)))))

It is fair to point out that, as recursion unfolds, stack frames will have to be set up, function arguments will have to be pushed into the stack, so on and so forth, resulting in unnecessary runtime overhead not experienced by the iterative counterpart of the above `factorial` function:

int factorial(int N) { int A = 1; while (N != 1) { A = A * N; N = N - 1; } return A; }

Because of this and other excuses, programmers conclude that they could write off recursive implementations …

Modern compilers for functional programming languages usually implement *tail-recursive call optimizations* which automatically translate a certain kind of linear recursion into efficient iterations. A linear recursive function is *tail-recursive* if the result of each recursive call is returned right away as the value of the function. Let’s examine the implementation of `fast-factorial` again:

(defun fast-factorial (N) "A tail-recursive version of factorial." (fast-factorial-aux N 1)) (defun fast-factorial-aux (N A) "Multiply A by the factorial of N." (if (= N 1) A (fast-factorial-aux (- N 1) (* N A))))

Notice that, in `fast-factorial-aux`, there is no work left to be done after the recursive call `(fast-factorial-aux (- N 1) (* N A))`. Consequently, the compiler will not create new stack frame or push arguments, but instead simply bind `(- N 1)` to `N` and `(* N A)` to `A`, and jump to the beginning of the function. Such optimization effectively renders `fast-factorial` as efficient as its iterative counterpart. Notice also the striking structural similarity between the two.

When you implement linearly recursive functions, you are encouraged to restructure it as a tail recursion after you have fully debugged your implementation. Doing so allows the compiler to optimize away stack management code. However, you should do so only after you get the prototype function correctly implemented. Notice that the technique of accumulator variables can be used even when we are not transforming code to tail recursions. For some problems, the use of accumulator variables offers the most natural solutions.

Feng上课的时候光听了这个结论，现在看看这篇文章才稍微懂了一点…原来是modern compiler的功劳，把tail recursive转成了iterative，因此使得迭代和循环效率一样