A visual introduction to big O notation

O(1) in many cases involves a hashing function which is a non-trivial but constant cost. For smaller values of N it can be outperformed in terms of wall clock time by n^2 worst case algorithms.

I mean, true obviously, but don't say that too loud lest people get the wrong ideas. For most practical purposes n^2 means computer stops working here. Getting people to understand that is hard enough already ;)

Besides, often you're lucky and there's a trivial perfect hash like modulo.

N^2 is just two nested loops. It trivially shows up everywhere you have 2D arrays.

Do I really need to make my code spaghetti if the array sizes are small enough to not impact my speed ?