Algorithms Analysis Practice Test 2025 – All-in-One Mastery Guide to Exam Success

Merge sort is an excellent example of an algorithm that employs a divide-and-conquer approach. The divide-and-conquer strategy consists of three main steps: dividing the problem into smaller subproblems, solving each subproblem independently, and then combining the solutions of the subproblems to solve the original problem.

In the case of merge sort, the algorithm begins by dividing the unsorted array into two halves recursively until each subarray contains a single element. Since an array with one element is considered sorted, the algorithm can then merge these smaller sorted subarrays back together. The merging step involves comparing the elements from each half and assembling them in sorted order, thus gradually combining the results back into a fully sorted array.

This method is efficient and works well with large datasets because it effectively reduces the complexity of sorting through systematic halving and merging. The overall time complexity of merge sort is O(n log n), making it a performant choice for sorting operations, particularly with large lists or arrays.