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In computer science, merge sort (also commonly spelled as mergesort and as merge-sort [2]) is an efficient, general-purpose, and comparison-based sorting algorithm. Most implementations produce a stable sort , which means that the relative order of equal elements is the same in the input and output.
Recursion: Some algorithms are either recursive or non-recursive, while others may be both (e.g., merge sort). Stability: stable sorting algorithms maintain the relative order of records with equal keys (i.e., values). Whether or not they are a comparison sort. A comparison sort examines the data only by comparing two elements with a comparison ...
Stable sorting algorithms maintain the relative order of records with equal keys (i.e. values). That is, a sorting algorithm is stable if whenever there are two records R and S with the same key and with R appearing before S in the original list, R will appear before S in the sorted list.
Repeatedly merge sublists to create a new sorted sublist until the single list contains all elements. The single list is the sorted list. The merge algorithm is used repeatedly in the merge sort algorithm. An example merge sort is given in the illustration. It starts with an unsorted array of 7 integers. The array is divided into 7 partitions ...
Block sort, or block merge sort, is a sorting algorithm combining at least two merge operations with an insertion sort to arrive at O(n log n) (see Big O notation) in-place stable sorting time. It gets its name from the observation that merging two sorted lists, A and B , is equivalent to breaking A into evenly sized blocks , inserting each A ...
Merge sort's requirement for Ω(n) extra space (roughly half the size of the input) is usually prohibitive except in the situations where merge sort has a clear advantage: When a stable sort is required; When taking advantage of (partially) pre-sorted input; Sorting linked lists (in which case merge sort requires minimal extra space)
Batcher's odd–even mergesort [1] is a generic construction devised by Ken Batcher for sorting networks of size O(n (log n) 2) and depth O((log n) 2), where n is the number of items to be sorted. Although it is not asymptotically optimal, Knuth concluded in 1998, with respect to the AKS network that "Batcher's method is much better, unless n ...
Comparison-based sorting algorithms have traditionally dealt with achieving an optimal bound of O(n log n) when dealing with time complexity.Adaptive sort takes advantage of the existing order of the input to try to achieve better times, so that the time taken by the algorithm to sort is a smoothly growing function of the size of the sequence and the disorder in the sequence.