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  2. Maximum subarray problem - Wikipedia

    en.wikipedia.org/wiki/Maximum_subarray_problem

    For example, for the array of values [−2, 1, −3, 4, −1, 2, 1, −5, 4], the contiguous subarray with the largest sum is [4, −1, 2, 1], with sum 6. Some properties of this problem are: If the array contains all non-negative numbers, then the problem is trivial; a maximum subarray is the entire array.

  3. Longest increasing subsequence - Wikipedia

    en.wikipedia.org/wiki/Longest_increasing_subsequence

    The longest increasing subsequences are studied in the context of various disciplines related to mathematics, including algorithmics, random matrix theory, representation theory, and physics. [ 1 ] [ 2 ] The longest increasing subsequence problem is solvable in time O ( n log ⁡ n ) , {\displaystyle O(n\log n),} where n {\displaystyle n ...

  4. Patience sorting - Wikipedia

    en.wikipedia.org/wiki/Patience_sorting

    Given an array of n elements from some totally ordered domain, consider this array as a collection of cards and simulate the patience sorting game. When the game is over, recover the sorted sequence by repeatedly picking off the minimum visible card; in other words, perform a k -way merge of the p piles, each of which is internally sorted.

  5. Timsort - Wikipedia

    en.wikipedia.org/wiki/Timsort

    The final algorithm takes the six most significant bits of the size of the array, adds one if any of the remaining bits are set, and uses that result as the minrun. This algorithm works for all arrays, including those smaller than 64; for arrays of size 63 or less, this sets minrun equal to the array size and Timsort reduces to an insertion sort.

  6. Prefix sum - Wikipedia

    en.wikipedia.org/wiki/Prefix_sum

    Prefix sums are trivial to compute in sequential models of computation, by using the formula y i = y i − 1 + x i to compute each output value in sequence order. However, despite their ease of computation, prefix sums are a useful primitive in certain algorithms such as counting sort, [1] [2] and they form the basis of the scan higher-order function in functional programming languages.

  7. Merge sort - Wikipedia

    en.wikipedia.org/wiki/Merge_sort

    In computer science, Merge Sort (also commonly spelled as mergesort and as merge-sort [2]) is an efficient, general-purpose, and comparison-based sorting algorithm.Most implementations produce a stable sort, which means that the relative order of equal elements is the same in the input and output.

  8. Subsequence - Wikipedia

    en.wikipedia.org/wiki/Subsequence

    Subsequences can contain consecutive elements which were not consecutive in the original sequence. A subsequence which consists of a consecutive run of elements from the original sequence, such as ,, , from ,,,,, , is a substring. The substring is a refinement of the subsequence.

  9. Longest common subsequence - Wikipedia

    en.wikipedia.org/wiki/Longest_common_subsequence

    The final result is that the last cell contains all the longest subsequences common to (AGCAT) and (GAC); these are (AC), (GC), and (GA). The table also shows the longest common subsequences for every possible pair of prefixes. For example, for (AGC) and (GA), the longest common subsequence are (A) and (G).