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Conceptually, the merge sort algorithm consists of two steps: Recursively divide the list into sublists of (roughly) equal length, until each sublist contains only one element, or in the case of iterative (bottom up) merge sort, consider a list of n elements as n sub-lists of size 1. A list containing a single element is, by definition, sorted.
If the running time (number of comparisons) of merge sort for a list of length n is T(n), then the recurrence relation T(n) = 2T(n/2) + n follows from the definition of the algorithm (apply the algorithm to two lists of half the size of the original list, and add the n steps taken to merge the resulting two lists). [5]
The classic merge outputs the data item with the lowest key at each step; given some sorted lists, it produces a sorted list containing all the elements in any of the input lists, and it does so in time proportional to the sum of the lengths of the input lists. Denote by A[1..p] and B[1..q] two arrays sorted in increasing order.
Problems of sufficient simplicity are solved directly. For example, to sort a given list of n natural numbers, split it into two lists of about n/2 numbers each, sort each of them in turn, and interleave both results appropriately to obtain the sorted version of the given list (see the picture). This approach is known as the merge sort algorithm.
balanced k-way merge sort; balanced merge sort; balanced multiway merge; balanced multiway tree; balanced quicksort; balanced tree; balanced two-way merge sort; BANG file; Batcher sort; Baum Welch algorithm; BB α tree; BDD; BD-tree; Bellman–Ford algorithm; Benford's law; best case; best-case cost; best-first search; biconnected component ...
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 ...
The previous example is a two-pass sort: first sort, then merge. The sort ends with a single k-way merge, rather than a series of two-way merge passes as in a typical in-memory merge sort. This is because each merge pass reads and writes every value from and to disk, so reducing the number of passes more than compensates for the additional cost ...
The sub-list is then merged into a new list. [1] Repeat this process and merge all sub-lists until all elements are sorted. [1] This algorithm is called strand sort because there are strands of sorted elements within the unsorted elements that are removed one at a time. [1] This algorithm is also used in J Sort for fewer than 40 elements. [2]