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  2. Longest common substring - Wikipedia

    en.wikipedia.org/wiki/Longest_common_substring

    This algorithm runs in () time. The array L stores the length of the longest common suffix of the prefixes S[1..i] and T[1..j] which end at position i and j, respectively. The variable z is used to hold the length of the longest common substring found so far.

  3. Hunt–Szymanski algorithm - Wikipedia

    en.wikipedia.org/wiki/Hunt–Szymanski_algorithm

    In computer science, the Hunt–Szymanski algorithm, [1] [2] also known as Hunt–McIlroy algorithm, is a solution to the longest common subsequence problem. It was one of the first non-heuristic algorithms used in diff which compares a pair of files each represented as a sequence of lines.

  4. LeetCode - Wikipedia

    en.wikipedia.org/wiki/LeetCode

    LeetCode LLC, doing business as LeetCode, is an online platform for coding interview preparation. The platform provides coding and algorithmic problems intended for users to practice coding . [ 1 ] LeetCode has gained popularity among job seekers in the software industry and coding enthusiasts as a resource for technical interviews and coding ...

  5. Longest common subsequence - Wikipedia

    en.wikipedia.org/wiki/Longest_common_subsequence

    Chowdhury and Ramachandran devised a quadratic-time linear-space algorithm [9] [10] for finding the LCS length along with an optimal sequence which runs faster than Hirschberg's algorithm in practice due to its superior cache performance. [9] The algorithm has an asymptotically optimal cache complexity under the Ideal cache model. [11]

  6. Subset sum problem - Wikipedia

    en.wikipedia.org/wiki/Subset_sum_problem

    The subset sum problem (SSP) is a decision problem in computer science. In its most general formulation, there is a multiset S {\displaystyle S} of integers and a target-sum T {\displaystyle T} , and the question is to decide whether any subset of the integers sum to precisely T {\displaystyle T} . [ 1 ]

  7. de Bruijn sequence - Wikipedia

    en.wikipedia.org/wiki/De_Bruijn_sequence

    The following Python code calculates a de Bruijn sequence, given k and n, based on an algorithm from Frank Ruskey's Combinatorial Generation. [ 10 ] from typing import Iterable , Any def de_bruijn ( k : Iterable [ str ] | int , n : int ) -> str : """de Bruijn sequence for alphabet k and subsequences of length n.

  8. LCP array - Wikipedia

    en.wikipedia.org/wiki/LCP_array

    Thus, every problem that can be solved by suffix tree algorithms can also be solved using the enhanced suffix array. [ 2 ] Deciding if a pattern P {\displaystyle P} of length m {\displaystyle m} is a substring of a string S {\displaystyle S} of length n {\displaystyle n} takes O ( m log ⁡ n ) {\displaystyle O(m\log n)} time if only the suffix ...

  9. Range query (computer science) - Wikipedia

    en.wikipedia.org/wiki/Range_query_(computer_science)

    One of the most famous algorithms for finding the majority of an array was proposed by Boyer and Moore [9] which is also known as the Boyer–Moore majority vote algorithm. Boyer and Moore proposed an algorithm to find the majority element of a string (if it has one) in O ( n ) {\displaystyle O(n)} time and using O ( 1 ) {\displaystyle O(1)} space.