How is tail call optimization used in functional programming?

1 What is a tail call?

A tail call is a function call that occurs as the last action of another function. For example, in the following code, the function foo calls the function bar as its last action, so bar is a tail call.

function foo(x) {
  return bar(x + 1);
}        

A tail call does not need to return the result of the called function, it can also perform some calculation or operation on it. For example, in the following code, the function baz calls the function qux as its last action, but also multiplies its result by 2, so qux is still a tail call.

function baz(x) {
  return 2 * qux(x - 1);
}        

3 Why is tail call optimization useful for functional programming?

Tail call optimization is useful for functional programming because it enables the use of recursion as a substitute for loops and iteration. Recursion is a natural way of expressing algorithms that involve breaking down a problem into smaller subproblems, or applying a function repeatedly until a base case is reached. Recursion also preserves the purity and immutability of functions, since no variables are mutated or reassigned in the process. However, recursion can be costly in terms of memory and performance, especially for large or infinite inputs. Tail call optimization solves this problem by making recursion as efficient as iteration, without losing the benefits of functional programming.

4 How to use tail call optimization in functional programming?

To use tail call optimization in functional programming, you need to follow two main rules. First, you need to write your functions in a tail-recursive form, which means that the recursive call must be the last action of the function, and it must return the result of the call directly or after some simple calculation. Second, you need to use a compiler or interpreter that supports tail call optimization, or a library or tool that implements it. For example, in JavaScript, tail call optimization is not supported by most engines, but you can use a transpiler like Babel or a library like Ramda to enable it.

5 What are the challenges and limitations of tail call optimization?

Tail call optimization is not a silver bullet for functional programming, and it has some challenges and limitations. One of the challenges is that not all languages or platforms support it, or they support it only partially or under certain conditions. For example, in Python, tail call optimization is not supported at all, and in Java, it is supported only for self-recursive calls. Another challenge is that tail call optimization can make debugging and tracing harder, since the stack trace does not show the full history of the function calls. One of the limitations is that tail call optimization does not work for non-tail recursive functions, which means that some algorithms or problems cannot be solved using this technique. For example, in the following code, the function pow calculates the power of a base using recursion, but it is not tail recursive, since the recursive call is not the last action of the function, and it does not return the result of the call directly.

function pow(base, exp) {
  if (exp === 0) return 1;
  return base * pow(base, exp - 1);
}        

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?