> If swaps are the only thing you are counting, selection sort is O(n).

And if you ignore the bottom half of the centaur, it's just a dude playing a flute. :)

"In computer science, the time complexity is the computational complexity that describes the amount of time it takes to run an algorithm." [1] We shouldn't be confusing people that actually want to learn about this stuff.

[1] https://en.wikipedia.org/wiki/Time_complexity

> And if you ignore the bottom half of the centaur, it's just a dude playing a flute. :)

That is an excellent phrase.

> We shouldn't be confusing people that actually want to learn about this stuff.

I definitely agree that Selection sort should definitely not be described as O(n) to beginners. I was just pointing out a subtly. In the strange case where memory writes are much more expensive than reads or comparisons, it is correct to say the Selection sort takes O(n) time.

I'm not sure what conditions you have in mind, but in the selection sort, the comparisons are O(n^2), and the assignments are O(n).

If comparisons are a fixed, non-zero cost, and assignments are a fixed, non-zero cost, then the comparisons in your selection sort will always overwhelm the assignments, and I can tell you at exactly which input size.

https://gist.github.com/mrami4/56d6e234f34787b8c5daf543a299a...

> And if you ignore the bottom half of the centaur, it's just a dude playing a flute. :)

Good one, but you probably meant Satyr (or Faun as Romans called it)

Centaurs are multifaceted and live rich, complex inner lives.

https://commons.wikimedia.org/wiki/File:Achilleus_Lyra.jpg#/...

The article describes these algorithms "efficient" on the basis of being linear, and they're not. Insertion and selection require O(n^2) moves or compares respectively (or, n log(n) with use of data structures). As it stands, the page is pretty as heck but teaching a misconception.

> The article describes these algorithms "efficient" on the basis of being linear, and they're not.

If memory writes are expensive (relative to reads and comparisons), selection sort is much better than insertion and bubble sort. Which is not something I had considered before trying to defend the post from the original comment.

> Insertion and selection require O(n^2) moves or compares respectively (or, n log(n) with use of data structures). As it stands, the page is pretty as heck but teaching a misconception.

I am definitely aware of the runtime of the sorting algorithms discussed. I have written about all of them [0]. Originally, I was going to agree and write about how it was a concerning misconception, but at least in the case of selection sort there is some (albeit small) merit to considering selection sort as O(n).

Though given that I cannot come up with a defense for insertion sort it is likely the author doesn't understand the time complexity of the sorting algorithms presented.

[0]: http://thethirdone.github.io/blog/posts/random-sorting/

Great article. Thanks for posting.