Understanding Mergesort: Sorting Made Simple | Recursion Series

Mergesort is a well-known and efficient sorting algorithm that follows the divide-and-conquer paradigm. It aims to sort a given array or list of elements by dividing it into smaller subarrays, sorting those subarrays recursively, and then merging them back together to obtain the final sorted result. The algorithm begins by repeatedly dividing the input array into two halves until each subarray contains only one element or is empty. This process is known as the "divide" step. Then, it merges adjacent pairs of these subarrays, comparing and rearranging the elements in a sorted order. This merging process continues until a single sorted array is obtained, hence the term "merge" in mergesort. One of the key advantages of mergesort is its stability, meaning that elements with equal values retain their original relative order after sorting. This property makes mergesort particularly useful in scenarios where preserving the original order of equal elements is crucial. Mergesort exhibits a time complexity of O(n log n), where "n" represents the number of elements in the input array. This efficiency makes mergesort suitable for sorting large datasets, and it is often used as a standard benchmark for other sorting algorithms. Overall, mergesort's simplicity, stability, and efficient performance have made it a popular choice in various applications, ranging from general-purpose sorting to applications in data analysis, parallel computing, and more. 0:00 Mergesort overview 2:15 Algorithm animation 3:35 The divide phase 5:10 The conquer phase 5:53 Mergesort pseudocode 7:46 Merge function Source code repository: https://github.com/williamfiset/algorithms Video slides: https://github.com/williamfiset/algorithms/tree/master/slides