What is the complexity of the algorithm in terms of time and memory?

Time Complexity of an algorithm describes how the number of operations grows depending on the size of the input data. It is usually expressed in Big O notation, for example, O(1), O(n), O(n²).

Space Complexity shows how much additional memory the algorithm requires depending on the input data.

Example: Bubble sort has a time complexity of O(n²) and a space complexity of O(1), as it sorts in place without additional memory.

In Go, as in any language, it is important to evaluate both metrics to choose the optimal solution.