Big O notation is a way to characterize the time or resources needed to solve a computing problem. It's particularly useful in comparing various computing algorithms under consideration. Below is a table summarizing Big O functions. The four most commonly referenced and important to remember are:
- O(1) Constant access time such as the use of a hash table.
- O(log n) Logarithmic access time such as a binary search of a sorted table.
- O(n) Linear access time such as the search of an unsorted list.
- O(n log(n)) Multiple of log(n) access time such as using Quicksort or Mergesort.