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  2. Ackermann function - Wikipedia

    en.wikipedia.org/wiki/Ackermann_function

    The inverse of the Ackermann function appears in some time complexity results. For instance, the disjoint-set data structure takes amortized time per operation proportional to the inverse Ackermann function, [ 24 ] and cannot be made faster within the cell-probe model of computational complexity.

  3. Strand sort - Wikipedia

    en.wikipedia.org/wiki/Strand_sort

    Strand sort is a recursive sorting algorithm that sorts items of a list into increasing order. It has O(n 2) worst-case time complexity, which occurs when the input list is reverse sorted. [1] It has a best-case time complexity of O(n), which occurs when the input is already sorted. [citation needed]

  4. Algorithmic efficiency - Wikipedia

    en.wikipedia.org/wiki/Algorithmic_efficiency

    Timsort sorts the list in time linearithmic (proportional to a quantity times its logarithm) in the list's length ((⁡)), but has a space requirement linear in the length of the list (()). If large lists must be sorted at high speed for a given application, timsort is a better choice; however, if minimizing the memory footprint of the sorting ...

  5. Computational complexity of mathematical operations - Wikipedia

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

    Here, complexity refers to the time complexity of performing computations on a multitape Turing machine. [1] See big O notation for an explanation of the notation used. Note: Due to the variety of multiplication algorithms, () below stands in for the complexity of the chosen multiplication algorithm.

  6. Time complexity - Wikipedia

    en.wikipedia.org/wiki/Time_complexity

    [1]: 226 Since this function is generally difficult to compute exactly, and the running time for small inputs is usually not consequential, one commonly focuses on the behavior of the complexity when the input size increases—that is, the asymptotic behavior of the complexity. Therefore, the time complexity is commonly expressed using big O ...

  7. Bogosort - Wikipedia

    en.wikipedia.org/wiki/Bogosort

    At recursion level k = 0, badsort merely uses a common sorting algorithm, such as bubblesort, to sort its inputs and return the sorted list. That is to say, badsort(L, 0) = bubblesort(L). Therefore, badsort's time complexity is O(n 2) if k = 0. However, for any k > 0, badsort(L, k) first generates P, the list of all permutations of L.

  8. Quicksort - Wikipedia

    en.wikipedia.org/wiki/Quicksort

    The outline of a formal proof of the O(n log n) expected time complexity follows. Assume that there are no duplicates as duplicates could be handled with linear time pre- and post-processing, or considered cases easier than the analyzed. When the input is a random permutation, the rank of the pivot is uniform random from 0 to n − 1.

  9. Bubble sort - Wikipedia

    en.wikipedia.org/wiki/Bubble_sort

    Bubble sort, sometimes referred to as sinking sort, is a simple sorting algorithm that repeatedly steps through the input list element by element, comparing the current element with the one after it, swapping their values if needed.