I find that the biggest misunderstanding happens because "new grads" (and I happen to be one) confuse _asymptotic complexity_ with actual complexity. I'm not sure sure why, but CS courses and interview questions mostly focus on _asymptotic complexity_ and usually forget to take into consideration the complexity for "little values of n". And funnily enough, in real life n never goes to infinity! In a strict sense big…
After a few years working on real-world code, I understood that faster asymptotic complexity was often slower on average. After a few more years working on real-world code, I understood that it's usually better to choose the algorithm with better asymptotic complexity, anyway. Like, sure, my O(n) algorithm will be 10x slower than your O(n^2) algorithm for small n. But users aren't going to notice a few microseconds.…
Re: New Grad vs. Senior Dev
#381It's a tough call sometimes. Code legibility is important and an O(n^2) is so often fast enough (microseconds!) that a more complex algorithm may be faster for the 0.001%ile and you're right that sometimes that means we should select it, because it makes the worst case still microseconds, but realistically speaking some codepaths change frequently enough that the true metric of a codebase is how easily it's adapted, understood, or modified. Let the guy with the big n eat cake, so to speak.