> (...) but as "describing how performance changes as the size of the input data increases".
Yes, that's the definition of asymptotic computational complexity. That's the whole point of these comparisons. It's pointless to compare algorithms when input size is in the single digit scale.
You could have an O(N^2) algorithm outperform an O(N) on the scale of 10,000 (or whatever scale you want to imagine). The big-O notation compares only asymptotic behaviour, and sometimes the lower power factors are overwhelming.
Yes, that's the definition of asymptotic computational complexity. That's the whole point of these comparisons. It's pointless to compare algorithms when input size is in the single digit scale.