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  2. Quicksort - Wikipedia

    en.wikipedia.org/wiki/Quicksort

    Quicksort is an efficient, general-purpose sorting algorithm. Quicksort was developed by British computer scientist Tony Hoare in 1959 [1] and published in 1961. [2] It is still a commonly used algorithm for sorting. Overall, it is slightly faster than merge sort and heapsort for randomized data, particularly on larger distributions. [3]

  3. Sorting algorithm - Wikipedia

    en.wikipedia.org/wiki/Sorting_algorithm

    Efficient implementations of quicksort (with in-place partitioning) are typically unstable sorts and somewhat complex but are among the fastest sorting algorithms in practice. Together with its modest O(log n) space usage, quicksort is one of the most popular sorting algorithms and is available in many standard programming libraries.

  4. Talk:Quicksort/Archive 1 - Wikipedia

    en.wikipedia.org/wiki/Talk:Quicksort/Archive_1

    Quicksort can actually be done in O(n log n) time worst case, by carefully choosing the pivot - the algorithm to do so is a bit complex though.

  5. Talk:Quicksort - Wikipedia

    en.wikipedia.org/wiki/Talk:Quicksort

    While the Quick Sort article gives people the view of the quick sort algorithm, we can update some new findings to it to make it stay up to the new research. For example, when changing the pick of pivots will improve the worst case of time complexity from O(N^2) to O(NlogN). MiaoQiQi 20:55, 14 March 2023 (UTC)

  6. Talk:Sorting algorithm - Wikipedia

    en.wikipedia.org/wiki/Talk:Sorting_algorithm

    Saying a sorting algorithm is O(nlogn) allows the execution with particular input to be less than nlogn; bubble sort taking n comparisons is not a surprise; it does not contradict the bound. Some algorithms are strictly Θ(nlogn).

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  8. Computational complexity theory - Wikipedia

    en.wikipedia.org/wiki/Computational_complexity...

    For example, the deterministic sorting algorithm quicksort addresses the problem of sorting a list of integers. The worst-case is when the pivot is always the largest or smallest value in the list (so the list is never divided). In this case, the algorithm takes time O().

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