Merge algorithms are a family of algorithms that take multiple sorted lists as input and produce a single list as output, containing all the elements of the inputs lists in sorted order. These algorithms are used as subroutines in various sorting algorithms, most famously merge sort.
The merge algorithm plays a critical role in the merge sort algorithm, a comparison-based sorting algorithm. 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.
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; each partition contains 1 element and is sorted. The sorted partitions are then merged to produce larger, sorted, partitions, until 1 partition, the sorted array, is left.
Merging two sorted lists into one can be done in linear time and linear or constant space (depending on the data access model). The following pseudocode demonstrates an algorithm that merges input lists (either linked lists or arrays) A and B into a new list C. The function yields the first element of a list; "dropping" an element means removing it from its list, typically by incrementing a pointer or index.
algorithm merge(A, B) is
inputs A, B : list
returns list
C := new empty list
while A is not empty and B is not empty do
if head(A) ≤ head(B) then
append head(A) to C
drop the head of A
else
append head(B) to C
drop the head of B
// By now, either A or B is empty. It remains to empty the other input list.
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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. Efficient sorting is important for optimizing the efficiency of other algorithms (such as search and merge algorithms) that require input data to be in sorted lists. Sorting is also often useful for canonicalizing data and for producing human-readable output.
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