Big O is a metric that measures the relationship between the number of steps that the execution of an algorithm requires in relationship with the input. It measures the pattern or trend of an algorithm and how it would behave in the worst-case scenario when the input approaches infinity. In other words, Big-O addresses one question “How will my algorithm/code behave as my input grows?”.

Big-O notation is important because it shows how efficient your algorithm/code is. In this article we will talk about time complexity, and how we can measure the Big O of an algorithm.

#web-development #programming #javascript #software-engineering #beginner