The post is going to be an intuitive introduction to Big O notation. I am not going to be rigorous or mathematical in my approach. Big O indicates how an algorithm behaves when the size of the input changes. The behavior might be either the computation time or the storage required for computation. What Big … Continue reading Intuitive Introduction to Big O →