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Merge algorithm
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Merge algorithm
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:
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 head yields the first element of a list; "dropping" an element means removing it from its list, typically by incrementing a pointer or index.
When the inputs are linked lists, this algorithm can be implemented to use only a constant amount of working space; the pointers in the lists' nodes can be reused for bookkeeping and for constructing the final merged list.
In the merge sort algorithm, this subroutine is typically used to merge two sub-arrays A[lo..mid], A[mid+1..hi] of a single array A. This can be done by copying the sub-arrays into a temporary array, then applying the merge algorithm above. The allocation of a temporary array can be avoided, but at the expense of speed and programming ease. Various in-place merge algorithms have been devised, sometimes sacrificing the linear-time bound to produce an O(n log n) algorithm; see Merge sort § Variants for discussion.
k-way merging generalizes binary merging to an arbitrary number k of sorted input lists. Applications of k-way merging arise in various sorting algorithms, including patience sorting and an external sorting algorithm that divides its input into k = 1/M − 1 blocks that fit in memory, sorts these one by one, then merges these blocks.
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Merge algorithm AI simulator
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Merge algorithm
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:
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 head yields the first element of a list; "dropping" an element means removing it from its list, typically by incrementing a pointer or index.
When the inputs are linked lists, this algorithm can be implemented to use only a constant amount of working space; the pointers in the lists' nodes can be reused for bookkeeping and for constructing the final merged list.
In the merge sort algorithm, this subroutine is typically used to merge two sub-arrays A[lo..mid], A[mid+1..hi] of a single array A. This can be done by copying the sub-arrays into a temporary array, then applying the merge algorithm above. The allocation of a temporary array can be avoided, but at the expense of speed and programming ease. Various in-place merge algorithms have been devised, sometimes sacrificing the linear-time bound to produce an O(n log n) algorithm; see Merge sort § Variants for discussion.
k-way merging generalizes binary merging to an arbitrary number k of sorted input lists. Applications of k-way merging arise in various sorting algorithms, including patience sorting and an external sorting algorithm that divides its input into k = 1/M − 1 blocks that fit in memory, sorts these one by one, then merges these blocks.