9/28/2023 0 Comments Tail recursion![]() If you like this pattern, take a look at functional programming languages like Scala or Haskell. So I recommend it despite its shortcomings! And if the need arises, a recursive function can be refactored into an iterative version. And despite the stack overflow problem, it can be used in JavaScript as long as you don't recure too much. Recursion allows to implement complex logic easily. It is much more declarative than the iterative versions, and often shorter. Premature optimization is the root of all evil - Donald Knuth But remember, this is an optimization, and Probably the best high level description I have found for tail calls, recursive tail calls and tail call optimization is the blog postīy Dan Sugalski.Const quickSort = array => Īnd voilà! We just have an iterative version of QuickSort. This is because the last thing to happen in any of these functions is to call another function. This below function is TCOptimizable: def fact_h(n, acc): This function does things besides call another function in its return statement. ![]() summing the leaves of a binary tree genuinely. In traditional recursion, the recursive call returns some value and we use. In the last post, we learned the traditional recursion. In other words, the function call happens as a last operation in the function body. This optimization can make recursive calls take constant stack space, rather than explode.Įxample: this factorial function is not TCOptimizable: from dis import dis Very nice answer I think the Fibonacci 'double recursion' can be turned into pure tail-recursion because this particular problem can be solved in O(1)-space using an iterative solution, but (correct me if I'm wrong) not all problems that look similar to the initial Fibonacci recursion can be converted to pure tail-recursion in the same way - e.g. Tail recursion, as the name suggests, is a type of recursion where no computation is done after the return of the recursive call. In this case the optimization can be made that g just runs and returns whatever value it would have to the thing that called f. The key here is that f no longer needs stack space - it simply calls g and then returns whatever g would return. The only situation in which this happens is if the last instruction executed in a function f is a call to a function g (Note: g can be f). TCO (Tail Call Optimization) is the process by which a smart compiler can make a call to a function and take no additional stack space. ![]() We start with the obvious recursive definition unsigned fac(unsigned n)Īs we can see here, a sufficiently advanced optimizer can replace tail-recursion with iteration, which is far more efficient as you avoid function call overhead and only use a constant amount of stack space. Let's walk through a simple example: the factorial function implemented in C. ![]() This is not the case with the non-tail-recursive fact, and as such large values may cause a stack overflow. When the Scala compiler recognizes that it is a tail recursion, it. This means that even if I were to call (fact 1000000), I need only the same amount of space as (fact 3). This code implements tail recursive factorial because the recursive call is the last action. In contrast, the stack trace for the tail recursive factorial looks as follows: (fact 3)Īs you can see, we only need to keep track of the same amount of data for every call to fact-tail because we are simply returning the value we get right through to the top. As such, the stack looks as follows: (fact 3) The first function is not tail recursive because when the recursive call is made, the function needs to keep track of the multiplication it needs to do with the result after the call returns. Scheme is one of the few programming languages that guarantee in the spec that any implementation must provide this optimization, so here are two examples of the factorial function in Scheme: (define (fact x) The most common use is tail-recursion, where a recursive function written to take advantage of tail-call optimization can use constant stack space. Tail-call optimization is where you are able to avoid allocating a new stack frame for a function because the calling function will simply return the value that it gets from the called function. ![]()
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