I often here people talk about Big O which measures algorithms against each other
Does this measure clock cycles or space requirements.
If people want to contras
Big O is really just a measure of the growth of complexity based on growth of input. Two algorithms with are both O(n) may execute in vastly different times but their grown is linear with relation to the growth of the input.