13 Facts About Merge sort

In computer science, merge sort is an efficient, general-purpose, and comparison-based sorting algorithm.

Merge sort is a divide-and-conquer algorithm that was invented by John von Neumann in 1945.

Natural merge sort is similar to a bottom-up merge sort except that any naturally occurring runs in the input are exploited.

Merge sort is more efficient than quicksort for some types of lists if the data to be sorted can only be efficiently accessed sequentially, and is thus popular in languages such as Lisp, where sequentially accessed data structures are very common.

Unlike some implementations of quicksort, merge sort is a stable sort.

Variants of merge sort are primarily concerned with reducing the space complexity and the cost of copying.

An external merge sort is practical to run using disk or tape drives when the data to be sorted is too large to fit into memory.

Each of these subarrays is sorted with an in-place sorting algorithm such as insertion sort, to discourage memory swaps, and normal merge sort is then completed in the standard recursive fashion.

Some parallel merge sort algorithms are strongly related to the sequential top-down merge algorithm while others have a different general structure and use the K-way merge method.

Such a sort can perform well in practice when combined with a fast stable sequential sort, such as insertion sort, and a fast sequential merge as a base case for merging small arrays.

Multiway merge sort algorithm is very scalable through its high parallelization capability, which allows the use of many processors.

Merge sort was one of the first sorting algorithms where optimal speed up was achieved, with Richard Cole using a clever subsampling algorithm to ensure O merge.

Merge sort is often the best choice for sorting a linked list: in this situation it is relatively easy to implement a merge sort in such a way that it requires only T extra space, and the slow random-access performance of a linked list makes some other algorithms perform poorly, and others completely impossible.