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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.
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 ...
Timsort is a hybrid, stable sorting algorithm, derived from merge sort and insertion sort, designed to perform well on many kinds of real-world data. It was implemented by Tim Peters in 2002 for use in the Python programming language. The algorithm finds subsequences of the data that are already ordered (runs) and uses them to sort the ...
Merge sort. In computer science, a sorting algorithm is an algorithm that puts elements of a list into an order.The most frequently used orders are numerical order and lexicographical order, and either ascending or descending.
k-way merge algorithms usually take place in the second stage of external sorting algorithms, much like they do for merge sort. A multiway merge allows for the files outside of memory to be merged in fewer passes than in a binary merge. If there are 6 runs that need be merged then a binary merge would need to take 3 merge passes, as opposed to ...
The sorting numbers fluctuate between and , with the same leading term but a worse constant factor in the lower-order linear term. [1] Merge-insertion sort is the sorting algorithm with the minimum possible comparisons for items whenever , and it has the fewest comparisons known for .
The running time is of order (), since there are subsets and, to check each subset, we need to sum at most n elements. The algorithm can be implemented by depth-first search of a binary tree: each level in the tree corresponds to an input number; the left branch corresponds to excluding the number from the set, and the right branch corresponds ...
The top down merge sort example (for arrays) avoids copy back by changing the direction of merge for each level of recursion (it does do an initial copy, but mutually recursive functions can be used to avoid the initial copy). The bottom up merge sort example mentions this in a comment that swapping pointers would avoid the shown copy back loop.