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  2. Pancake sorting - Wikipedia

    en.wikipedia.org/wiki/Pancake_sorting

    Pancake sorting is the mathematical problem of sorting a disordered stack of pancakes in order of size when a spatula can be inserted at any point in the stack and used to flip all pancakes above it. A pancake number is the minimum number of flips required for a given number of pancakes.

  3. Insertion sort - Wikipedia

    en.wikipedia.org/wiki/Insertion_sort

    Insertion sort is a simple sorting algorithm that builds the final sorted array (or list) one item at a time by comparisons. It is much less efficient on large lists than more advanced algorithms such as quicksort, heapsort, or merge sort. However, insertion sort provides several advantages:

  4. Sorting algorithm - Wikipedia

    en.wikipedia.org/wiki/Sorting_algorithm

    This is a linear-time, analog algorithm for sorting a sequence of items, requiring O(n) stack space, and the sort is stable. This requires n parallel processors. See spaghetti sort#Analysis. Sorting network: Varies: Varies: Varies: Varies: Varies (stable sorting networks require more comparisons) Yes

  5. Comb sort - Wikipedia

    en.wikipedia.org/wiki/Comb_sort

    Comb sort's passes do not completely sort the elements. This is the reason that Shellsort gap sequences have a larger optimal shrink factor of about 2.25. One additional refinement suggested by Lacey and Box is the "rule of 11": always use a gap size of 11, rounding up gap sizes of 9 or 10 (reached by dividing gaps of 12, 13 or 14 by 1.3) to 11.

  6. Shellsort - Wikipedia

    en.wikipedia.org/wiki/Shellsort

    The next pass, 3-sorting, performs insertion sort on the three subarrays (a 1, a 4, a 7, a 10), (a 2, a 5, a 8, a 11), (a 3, a 6, a 9, a 12). The last pass, 1-sorting, is an ordinary insertion sort of the entire array (a 1,..., a 12). As the example illustrates, the subarrays that Shellsort operates on are initially short; later they are longer ...

  7. Heapsort - Wikipedia

    en.wikipedia.org/wiki/Heapsort

    The heapsort algorithm can be divided into two phases: heap construction, and heap extraction. The heap is an implicit data structure which takes no space beyond the array of objects to be sorted; the array is interpreted as a complete binary tree where each array element is a node and each node's parent and child links are defined by simple arithmetic on the array indexes.

  8. 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]

  9. Sorting - Wikipedia

    en.wikipedia.org/wiki/Sorting

    Such a component or property is called a sort key. For example, the items are books, the sort key is the title, subject or author, and the order is alphabetical. A new sort key can be created from two or more sort keys by lexicographical order. The first is then called the primary sort key, the second the secondary sort key, etc.