What does the term 'Big O' represent in the context of time complexity analysis?

The term 'Big O' in the context of time complexity analysis is used to describe the worst-case scenario of an algorithm's performance. It provides an upper bound on the time required for an algorithm to complete based on the size of the input.

Here are the steps to understand it:

1. Identify the Algorithm: First, you need to identify the algorithm that you want to analyze. This could be a sorting algorithm, a search algorithm, or any other type of algorithm.

2. Determine the Worst-Case Scenario: Next, you need to determine the worst-case scenario for this algorithm. This is the situation where the algorithm would take the longest time to complete. For example, for a sorting algorithm, the