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  2. Luhn mod N algorithm - Wikipedia

    en.wikipedia.org/wiki/Luhn_mod_N_algorithm

    The Luhn mod N algorithm generates a check digit (more precisely, a check character) within the same range of valid characters as the input string. For example, if the algorithm is applied to a string of lower-case letters (a to z), the check character will also be a lower-case letter. Apart from this distinction, it resembles very closely the ...

  3. Hamming distance - Wikipedia

    en.wikipedia.org/wiki/Hamming_distance

    For a fixed length n, the Hamming distance is a metric on the set of the words of length n (also known as a Hamming space), as it fulfills the conditions of non-negativity, symmetry, the Hamming distance of two words is 0 if and only if the two words are identical, and it satisfies the triangle inequality as well: [2] Indeed, if we fix three words a, b and c, then whenever there is a ...

  4. Longest common substring - Wikipedia

    en.wikipedia.org/wiki/Longest_common_substring

    The longest common substrings of a set of strings can be found by building a generalized suffix tree for the strings, and then finding the deepest internal nodes which have leaf nodes from all the strings in the subtree below it. The figure on the right is the suffix tree for the strings "ABAB", "BABA" and "ABBA", padded with unique string ...

  5. Hamming weight - Wikipedia

    en.wikipedia.org/wiki/Hamming_weight

    In Python, the int type has a bit_count() method to count the number of bits set. This functionality was introduced in Python 3.10, released in October 2021. [17] In Common Lisp, the function logcount, given a non-negative integer, returns the number of 1 bits. (For negative integers it returns the number of 0 bits in 2's complement notation.)

  6. Levenshtein distance - Wikipedia

    en.wikipedia.org/wiki/Levenshtein_distance

    A more efficient method would never repeat the same distance calculation. For example, the Levenshtein distance of all possible suffixes might be stored in an array , where [] [] is the distance between the last characters of string s and the last characters of string t. The table is easy to construct one row at a time starting with row 0.

  7. LCP array - Wikipedia

    en.wikipedia.org/wiki/LCP_array

    Given the suffix array and the LCP array of a string =,, … $ of length +, its suffix tree can be constructed in () time based on the following idea: Start with the partial suffix tree for the lexicographically smallest suffix and repeatedly insert the other suffixes in the order given by the suffix array.

  8. Weight (strings) - Wikipedia

    en.wikipedia.org/wiki/Weight_(strings)

    The -weight of a string, for a letter , is the number of times that letter occurs in the string.More precisely, let be a finite set (called the alphabet), a letter of , and a string (where is the free monoid generated by the elements of , equivalently the set of strings, including the empty string, whose letters are from ).

  9. Edit distance - Wikipedia

    en.wikipedia.org/wiki/Edit_distance

    In computational linguistics and computer science, edit distance is a string metric, i.e. a way of quantifying how dissimilar two strings (e.g., words) are to one another, that is measured by counting the minimum number of operations required to transform one string into the other.