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  2. Longest common subsequence - Wikipedia

    en.wikipedia.org/wiki/Longest_common_subsequence

    The prefix S n of S is defined as the first n characters of S. [5] For example, the prefixes of S = (AGCA) are S 0 = S 1 = (A) S 2 = (AG) S 3 = (AGC) S 4 = (AGCA). Let LCS(X, Y) be a function that computes a longest subsequence common to X and Y. Such a function has two interesting properties.

  3. Chvátal–Sankoff constants - Wikipedia

    en.wikipedia.org/wiki/Chvátal–Sankoff_constants

    Compute a longest common subsequence of these two strings, and let , be the random variable whose value is the length of this subsequence. Then the expected value of λ n , k {\displaystyle \lambda _{n,k}} is (up to lower-order terms) proportional to n , and the k th Chvátal–Sankoff constant γ k {\displaystyle \gamma _{k}} is the constant ...

  4. Longest common substring - Wikipedia

    en.wikipedia.org/wiki/Longest_common_substring

    The set ret can be saved efficiently by just storing the index i, which is the last character of the longest common substring (of size z) instead of S[(i-z+1)..i]. Thus all the longest common substrings would be, for each i in ret, S[(ret[i]-z)..(ret[i])]. The following tricks can be used to reduce the memory usage of an implementation:

  5. 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.

  6. Levenshtein distance - Wikipedia

    en.wikipedia.org/wiki/Levenshtein_distance

    In information theory, linguistics, and computer science, the Levenshtein distance is a string metric for measuring the difference between two sequences. The Levenshtein distance between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the other.

  7. Longest increasing subsequence - Wikipedia

    en.wikipedia.org/wiki/Longest_increasing_subsequence

    The longest increasing subsequence has also been studied in the setting of online algorithms, in which the elements of a sequence of independent random variables with continuous distribution – or alternatively the elements of a random permutation – are presented one at a time to an algorithm that must decide whether to include or exclude ...

  8. Subsequence - Wikipedia

    en.wikipedia.org/wiki/Subsequence

    SEQ 1 = A CG G T G TCG T GCTATGCT GA T G CT G ACTTAT A T G CTA SEQ 2 = CGTTCGGCTAT C G TA C G TTCTA TT CT A T G ATT T CTA A. Another way to show this is to align the two sequences, that is, to position elements of the longest common subsequence in a same column (indicated by the vertical bar) and to introduce a special character (here, a dash ...

  9. Suffix tree - Wikipedia

    en.wikipedia.org/wiki/Suffix_tree

    Finding the longest repeated substring; Finding the longest common substring; Finding the longest palindrome in a string; Suffix trees are often used in bioinformatics applications, searching for patterns in DNA or protein sequences (which can be viewed as long strings of characters). The ability to search efficiently with mismatches might be ...