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Start of string Before all other characters on page $ End of string After all other characters on page (or line if multiline option is active) \Z: End of string After all other characters on page \b: On a word boundary On a letter, number or underscore character \B: Not on a word boundary Not on a letter, number or underscore character
A simple and inefficient way to see where one string occurs inside another is to check at each index, one by one. First, we see if there is a copy of the needle starting at the first character of the haystack; if not, we look to see if there's a copy of the needle starting at the second character of the haystack, and so forth.
The closeness of a match is measured in terms of the number of primitive operations necessary to convert the string into an exact match. This number is called the edit distance between the string and the pattern. The usual primitive operations are: [1] insertion: cot → coat; deletion: coat → cot; substitution: coat → cost
By wrapping part of the pattern in brackets, you can extract it, referencing it with the code %1. Example: The find-replace instruction {{#invoke:string|replace|AaAabc XYZ|^([Aa]*)b?c|%1|plain=false}} gives AaAa XYZ; We can discard the XYZ by putting .* at the end of the search string; this picks up anything after the rest of the pattern.
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.
S[i] denotes the character at index i of string S, counting from 1. S[i..j] denotes the substring of string S starting at index i and ending at j, inclusive. A prefix of S is a substring S[1..i] for some i in range [1, l], where l is the length of S. A suffix of S is a substring S[i..l] for some i in range [1, l], where l is the length of S.
String functions are used in computer programming languages to manipulate a string or query information about a string (some do both).. Most programming languages that have a string datatype will have some string functions although there may be other low-level ways within each language to handle strings directly.
A string-matching algorithm wants to find the starting index m in string S[] that matches the search word W[].. The most straightforward algorithm, known as the "brute-force" or "naive" algorithm, is to look for a word match at each index m, i.e. the position in the string being searched that corresponds to the character S[m].