Big O Notation and Algorithm Analysis with Python Examples
There are multiple ways to solve a problem using a computer program. For instance, there are several ways to sort items in an array. You can use merge sort, bubble sort, insertion sort, etc. All these algorithms have their own pros and cons. An algorithm can be thought of a procedure or formula to solve a particular problem. The question is, which algorithm to use to solve a specific problem when there exist multiple solutions to the problem?
Algorithm analysis refers to the analysis of the complexity of different algorithms and finding the most efficient algorithm to solve the problem at hand. Big-O Notation is a statistical measure, used to describe the complexity of the algorithm.
In this article, we will briefly review algorithm analysis and Big-O notation. We will see how Big-O notation can be used to find algorithm complexity with the help of different Python functions.
Why is Algorithm Analysis Important?
To understand why algorithm analysis is important, we will take help of a simple example.
Suppose a manager gives a task to two of his employees to design an algorithm in Python that