Search results
Results from the WOW.Com Content Network
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.
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; These three operations may be generalized as forms of substitution by adding a NULL character (here symbolized by *) wherever a character has been ...
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.
A regular expression (shortened as regex or regexp), [1] sometimes referred to as rational expression, [2] [3] is a sequence of characters that specifies a match pattern in text. Usually such patterns are used by string-searching algorithms for "find" or "find and replace" operations on strings, or for input validation.
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.
In computer science, the Knuth–Morris–Pratt algorithm (or KMP algorithm) is a string-searching algorithm that searches for occurrences of a "word" W within a main "text string" S by employing the observation that when a mismatch occurs, the word itself embodies sufficient information to determine where the next match could begin, thus bypassing re-examination of previously matched characters.
Replace and expand placeholders: creating a new string from the original one, by find–replace operations. Find variable reference (placeholder), replace it by its variable value. This algorithm offers no cache strategy. Split and join string: splitting the string into an array, merging it with the corresponding array of values, then joining ...