Writing a Pythonic Complexity Scanner
Competitive programming often reduces algorithmic efficiency to Big O notation. While theoretically sound, Big O ignores the constants, interpreter overhead, and memory allocation patterns inherent in actual execution. A solution might be O(N) on paper but fail runtime constraints due to Python’s specific implementation details. I developed Occam to bridge the gap between theoretical complexity and hardware reality. The goal was to build a local profiling tool capable of analyzing solution behavior under stress before submission to platforms like LeetCode. ...