Algorithm complexity

Algorithm complexity refers to how the time or resources needed to solve a problem grow as the size of that problem increases. It helps us understand the efficiency of an algorithm, which is a step-by-step procedure for solving a problem. There are two main types: time complexity, which measures how long an algorithm takes to run, and space complexity, which measures how much memory it uses. By analyzing complexity, we can predict performance and make informed choices about which algorithms to use, especially for large datasets or complex tasks.