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 O notation only cares about what happens when n goes to infinity. The algorithm could behave in any way up to numbers unimaginable (like TREE(3)) but still, its big O wouldn't change.
Maybe what is missing to those "new grad" is a felling of real world data, and how a computer behave in the real world (with caches, latencies, optimised instructions etc...) not just having an ideal computer model in their mind when they design algorithms.
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 O notation only cares about what happens when n goes to infinity. The algorithm could behave in any way up to numbers unimaginable (like TREE(3)) but still, its big O wouldn't change.
Maybe what is missing to those "new grad" is a felling of real world data, and how a computer behave in the real world (with caches, latencies, optimised instructions etc...) not just having an ideal computer model in their mind when they design algorithms.