For small sets, or small-ish sets when you are coding quick, don't have a convenient standard library sort to hand, and are prioritising correctness over absolute performance.

Though in reality almost never: you almost always have a convenient built-in sort that is as quick & easy to use (likely quicker & easier), and in circumstances where the set is small enough for bubblesort to be just fine, the speed, memory use, or other properties of what-ever other sort your standard library uses aren't going to be a problem either.

As others have pointed out, sometimes it is useful for partial sorts due to the “always no less sorted than before at any point in the process (assuming no changes due to external influence)” property.

wrt:

> If you make each frame of the animation one pass of bubblesort, the particles will all move smoothly into the right positions. I couldn't find any examples in the wild,

There are hundreds of sort demos out there, both live running and on publicly hosted videos, that show the final positions by hue, getting this effect. Seems odd that they couldn't find a single one.

EDIT: actually, I can't find any of the rainbow based sort demos I was thinking of, a lot of promising links seem dead. I take back my little moan!

Related to this is Timsort which combines merge sort and insertion sort https://en.wikipedia.org/wiki/Timsort

Can confirm, have used bubble sort for incrementally sorting particles in a particle system and plants in a terrain renderer.

bubble sort is sometimes used in information retrieval use cases for reranking top k based on some signals, especially specific to a user profile. I feel heap sort comes up as well, yet neither are necessarily the most efficient.

In all your big-O analyses, remember: n = 3 more often than you think. n = 12 a lot more often than you think. If that's your case, there's nothing wrong with bubble sort unless you have very tight performance constraints.

Worse, big-O always hides a constant factor. What's bubblesort's constant? What's quicksort's? It wouldn't surprise me if, for small enough n (2 or 3, and maybe a bit higher), bubblesort is actually faster.

Note well: I have not actually benchmarked this.

Also note well: Determine what your n is; don't assume that it's either large or small.

A: For small arrays. I would add: particularly if you need a stable sort algorithm, which is either complex (Block Sort) or uses O(n) space (Merge Sort).

Well, I used Bubblesort to sort the results of lottery draws because it was very easy to implement.

If you need a stable sort, can't be bothered finding a massive oversize library to link to, and only need to sort a relatively small number of objects on a system that's resource-constrained, I'm guessing?