Algorithms 101: commonly used time complexities from smallest to largest

The order of commonly used time complexities, from smallest to largest, is:

O(1) < O(logn) < O(n) < O(nlogn) < O(n^2) < O(n^3) < O(2^n) < O(n!) < O(n^k)

This order is determined based on the growth rate of commonly encountered time complexities. Time complexity represents the relationship between the time taken by an algorithm and the size of its input. In the given order, the time complexity gradually increases as the input size grows.

This sequence is derived from an analysis of search results, including code examples and explanations. It provides a relative comparison of commonly encountered time complexities.

Please note that this order represents commonly encountered time complexities and may not include all possible time complexities. In practice, there may be algorithms with different time complexities.