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Timsort, which combines Merge and Insertion sort to do exactly what you describe. It makes use of already sorted parts of the collection to speed sorting. Effectively it's a merge sort up till it finds enough "chunks" to use insertion sort. This gives it a worst case and average case time complexity of O(nlogn), same as the base merge sort. It gains the ...


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Note that the pseudo-code in wiki is not practical. It is written to undestand. If an array is [0,0,0,1] pivot is 1 and other elements are less than the pivot, then swapping(t <-- a, a <-- b, b <--t) works as t <-- a, a <-- a, a <-- t. In this case swapping works nothing. If an array is [4,2,1,3] then [4,2,1,3] --> [2,4,1,3] --> [2,1,4,3] ...


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An algorithm escapes from most bad cases using a randomized pivot, excluding continuous elements equals to a pivot from partitioning, and asymmetric search. It searches forward an element greater or equals to a pivot, and searches backward an element less than a pivot. I thank MichaelT, Asymmetric search is devised to resolve [2,1,2,1,2,1,2,1]. The ...



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