# Refactoring Asynchronous Recursion with Continuation-Passing Style

Posted on January 22, 2023

(This article was originally drafted in February 2022. The topic is very much related to the previous article’s, Implementing environment-based evaluation of recursive functions in OCaml, but they can very much be read independently.)

Whew, that’s a title that takes some unpacking! Asynchronous recursion is a concept in JavaScript, and presumably in other languages with some form of async-await. Maybe another way to call it would be “indirect recursion”. A picture is worth a thousand words, so let me paint a picture with some code. Let’s count down from a given number until we reach zero, pausing for a second at each recursive call.

function countdown(n) {
if (n <= 0) {
console.log(
"No more bottles of beer on the wall, no more bottles of beer!",
);
return;
}
console.log(${n} bottles of beer on the wall,${n} bottles of beer! ...);
setTimeout(() => countdown(n - 1), 1000);
}

This is what I mean by “asynchronous recursion” or “indirect recursion”. Rather than making a recursive call as a statement of the main body of countdown, the recursive call is made in a callback function to an asynchronous operation – in this case, a timeout.

This pattern of recursion can be converted to a kind of continuation-passing style (CPS). A JavaScript programmer is probably already intimately familiar with this style of programming. For example in NodeJS, most of the standard library works this way. Here’s an example where we delete a file:

const fs = require('fs');

if (err) { console.log('yikes'); return; }
console.log('deleted /tmp/hello');
});

What’s special about this is that the code to execute after the delete has taken place is represented as a function passed as the second parameter of unlink. The call to unlink returns immediately so other work can be done concurrently. When the deletion finishes, the NodeJS runtime invokes the callback we passed, and we see either “yikes” or “deleted /tmp/hello”.

From the internal implementation of unlink’s point of view, it has been passed a function that it can consider a “return function”. When unlink’s IO operation is finished, it would like to return back into our code, but because all of this happened asynchronously, there isn’t a stack frame in our code that we can simply return to! Instead, it calls the “return function” it was passed.

This concept of “return function” is an instance of taking a baked-in notion of control flow – in this case, returning from a function call – and reflecting it into our code as an explicit function we can call.

To refactor the example of asynchronous recursion I showed earlier, we can apply this same idea. Let’s take the control-flow idea of “making a recursive call” and reflect it into our code as an explicit function, by rewriting countdown to take an extra parameter which I’ll unimaginatively call recurse:

function countdown(recurse, n) {
if (n <= 0) {
console.log(
"No more bottles of beer on the wall, no more bottles of beer!",
);
return;
}
console.log(${n} bottles of beer on the wall,${n} bottles of beer! ...);

recurse(n - 1);
}

Notice that I also got rid of the setTimeout. The big idea here is that countdown doesn’t care what kind of recursion the caller wants. The caller can choose what to pass as recurse and get either synchronous or asynchronous recursion as desired! The accomplishment here is also a separation of concerns: we decoupled the behaviour for a single iteration of a recursive loop from the “loop behaviour”.

The change we made to countdown comes at a cost, however. What exactly are we supposed to put as a value for recurse when we call countdown??

To address this, we will model each kind of recursive behaviour as a separate, higher-order function to which we can pass countdown. The result of applying such a recursion combinator to countdown should be a function that takes all the “real” parameters of countdown, i.e. n. Let’s figure out how to implement a “standard” recursion first, then we’ll move on to asynchronous recursion.

const recursively = (f) => (...args) => f(recursively(f), ...args);

To see how this works, let’s evaluate recursively(countdown). There’s only one step to do: substitute countdown for f and we arrive at (...args) => countdown(recursively(countdown), ...args). The result is that when we call this function with a number such as 100, we in fact end up calling countdown passing recursively(countdown) itself as the argument for the recurse parameter. The process then continues recursively, we might say.

Finally, to make this asynchronous, we’ll need to construct a new recurse function that’s more complicated than just f. But only a bit more complicated. It will simply need to call itself within a call to setTimeout.

const delayedRecursively = (f, delay) =>
(...args) => f(
(...args) => setTimeout(
() => f(delayedRecursively(f, delay), ...args),
delay,
),
...args
);

Let’s convince ourselves that this works by evaluating delayedRecursively(countdown, 100). Substituting, we get

(...args) => countdown((...args) =>
setTimeout(() =>
countdown(delayedRecursively(countdown, 100), ...args), 100), ...args)

If we imagine for a moment that JavaScript allows partial application, then we can substitute further and get the following:

(n) => {
/* ... the countdown implementation ... */
setTimeout(() => countdown(delayedRecursively(countdown, 100), n-1), 100)
}

And if we ran this as delayedRecursively(countdown, 500)(10) we would see the messages printed out slowly.

This approach works! We were able to get different recursive behaviours out of the same implementation of countdown, provided it recurse through an auxiliary function rather than directly.

There is however a glaring issue with this approach: there is no way for the recursive call to meaningfully return a value to the caller! Sure, recursively simply returns whatever f returns, so one could simply write const result = recurse(...); but what about when we use delayedRecursively? We would then get whatever setTimeout returns! To address this, we will need a uniform way to return a value, that works whether the recursion is synchronous or asynchronous.

## Returning via yet another function

The trick, as always, is to introduce yet another layer of indirection.

As a motivating example, let’s consider a recursive algorithm that sums the integer values contained in a binary tree.

const sumTree = (t) => {
if (t === null) return 0;
else return sumTree(t.left) + t.value + sumTree(t.right);
}

First and as before, we make the recursion indirect via a recurse function.

const sumTree = (recurse, t) => {
if (t === null) return 0;
else return recurse(t.left) + t.value + recurse(t.right);
}

Next, we observe that we have a problem if we use delayedRecursively: the return value of recurse(t.left), for example, won’t be the sum of the left subtree’s elements! Let’s introduce another function parameter called resolve this time. Rather than returning via the return statement, our function will instead return by calling resolve.

const sumTree = (recurse, t, resolve) => {
if (t === null) resolve(0);
else
recurse(t.left, (n1) =>
recurse(t.right, (n2) =>
resolve(n1 + t.value + n2)));
}

What’s nice about this approach is that it works without us needing to modify any of our recursion combinators from the previous section. We can evaluate delayedRecursively(sumTree, 100)(sampleTree, (n) => console.log(n)) and it (slowly) calculates the sum of the tree and prints out the sum.

## Conclusion

In this article, we saw how to separate two concerns that at first glance seem inextricably tried: the pattern of recursion was isolated from the recursive algorithm itself. We introduced some combinators, recursively and delayedRecursively, to each represent a different pattern of recursion. Then, we rewrote our recursive algorithm to recurse via a function which we named recurse. That refactored version of the algorithm expresses the base and step cases of the recursive algorithm without explicitly performing the recursion, leaving it up to the recursion combinator to decide how exactly that will be done. Finally, to account for a desire to return values from our functions, we introduced one more layer of indirection by returning via a function which we named resolve. No changes to the recursion combinators were necessary to accommodate this.

The choice of resolve for the name of this function is no accident. The code recurse(t.left, (n1) => recurse(t.right, (n2) => resolve(n1 + t.value + n2))) is honestly gross. It’s callback hell. There is certainly a way of writing some slightly different recursion combinators that take advantage of JavaScript’s promises and async/await syntax. I leave it to the interested reader to work this out.