Big O Notation

The Big O notation can be used to describe how the running time of an algorithm scales with the growth of the input size, ignoring implementation details such as programming language and computer speed. Specifically, it denotes the upper bound of the growth rate of a function that relates the running time of an algorithm to its input size. It can be used to compare algorithms and determine which one is better.

Visit the following resources to learn more:

• @article@Big-O Notation: A Simple Explanation with Examples
• @article@CS 61B Lecture 19: Asymptotic Analysis
• @article@Big O Notation | Brilliant Math & Science Wiki
• @video@Big O Notation — Calculating Time Complexity
• @video@Big O Notations
• @video@Big Oh Notation (and Omega and Theta)