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  2. Merge algorithm - Wikipedia

    en.wikipedia.org/wiki/Merge_algorithm

    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. [1] The allocation of a temporary array can be avoided, but at the expense of speed and programming ease.

  3. Disjoint-set data structure - Wikipedia

    en.wikipedia.org/wiki/Disjoint-set_data_structure

    The precise analysis of the performance of a disjoint-set forest is somewhat intricate. However, there is a much simpler analysis that proves that the amortized time for any m Find or Union operations on a disjoint-set forest containing n objects is O(m log * n), where log * denotes the iterated logarithm. [12] [13] [14] [15]

  4. Divide-and-conquer algorithm - Wikipedia

    en.wikipedia.org/wiki/Divide-and-conquer_algorithm

    The divide-and-conquer technique is the basis of efficient algorithms for many problems, such as sorting (e.g., quicksort, merge sort), multiplying large numbers (e.g., the Karatsuba algorithm), finding the closest pair of points, syntactic analysis (e.g., top-down parsers), and computing the discrete Fourier transform . [1]

  5. Skew heap - Wikipedia

    en.wikipedia.org/wiki/Skew_heap

    Only two conditions must be satisfied: The general heap order must be enforced; Every operation (add, remove_min, merge) on two skew heaps must be done using a special skew heap merge. A skew heap is a self-adjusting form of a leftist heap which attempts to maintain balance by unconditionally swapping all nodes in the merge path when merging ...

  6. k-way merge algorithm - Wikipedia

    en.wikipedia.org/wiki/K-way_merge_algorithm

    The k-way merge problem consists of merging k sorted arrays to produce a single sorted array with the same elements.Denote by n the total number of elements. n is equal to the size of the output array and the sum of the sizes of the k input arrays.

  7. Bitonic sorter - Wikipedia

    en.wikipedia.org/wiki/Bitonic_sorter

    The green and blue boxes combine to form the entire sorting network. For any arbitrary sequence of inputs, it will sort them correctly, with the largest at the bottom. The output of each green or blue box will be a sorted sequence, so the output of each pair of adjacent lists will be bitonic, because the top one is blue and the bottom one is green.

  8. Timsort - Wikipedia

    en.wikipedia.org/wiki/Timsort

    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.

  9. Sorting algorithm - Wikipedia

    en.wikipedia.org/wiki/Sorting_algorithm

    Formally, the output of any sorting algorithm must satisfy two conditions: The output is in monotonic order (each element is no smaller/larger than the previous element, according to the required order). The output is a permutation (a reordering, yet retaining all of the original elements) of the input.