asymptotic analysis

Asymptotic analysis is a method used to describe how the performance of an algorithm or function behaves as its input size grows larger. Instead of focusing on exact execution times, it provides a way to understand the growth rate of the time or space required. Commonly expressed using "big O" notation, it helps to compare algorithms by highlighting their efficiency and scalability. For example, an algorithm that runs in O(n) time grows linearly with input size, while one that runs in O(n^2) time becomes significantly slower as more data is processed. This analysis is crucial for optimizing software performance.