Complexity

Algorithm complexity measures how the running time or memory usage of an algorithm grows as the size of its input increases. Big-O notation is the standard way to express this.

Space complexity describes how much memory an algorithm needs relative to its input size. Alongside time complexity, it helps you evaluate whether an algorithm is practical for a given situation.

Time complexity describes how the running time of an algorithm grows as the input size increases. Using Big O notation, you can compare algorithms and predict which will perform better on large datasets.