We may have used a similar technique in real life while sorting a huge number of boxes (or any object). We then sort the sublists and merge them to produce the sorted list. If the list length is odd, the size of the sublists differs by 1. The size of the two sublists is equal when the list is of even length. In the case of merge sort, at each step, we divide the list into two smaller sublists until the size of each list reduces to 1. The problem is divided into multiple subproblems, solved individually, and finally, the result of the subproblems are combined to form the final solution. Merge sort uses the concept of divide and conquer. Therefore, it’s not preferred for sorting an almost sorted array. Merge sort has a consistent speed for a given size of data. Most implementations of this algorithm produce a stable sort, i.e., i.e., the order of any two equal elements in the sorted list and the original list stays the same. Merge sort is a general-purpose comparison-based sorting algorithm - which means that the algorithm compares the elements of the list to sort it. In this article, we will help get one step closer to cracking that interview. Sorting algorithm questions are a big part of coding interviews at tech companies. If you are a software developer preparing for your next tech interview, then this one algorithm you must review. Merge sort is one of the most efficient and popular sorting algorithms.
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