I am learning about Big O Notation running times and amortized times. I understand the notion of O(n) linear time, meaning that the size of the input affects the g
It simply means that the time needed for this task grows with log(n) (example : 2s for n = 10, 4s for n = 100, ...). Read the Wikipedia articles on Binary Search Algorithm and Big O Notation for more precisions.