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Regular Expression Flavor Comparison – Detailed comparison of the most popular regular expression flavors; Regexp Syntax Summary; Online Regular Expression Testing – with support for Java, JavaScript, .Net, PHP, Python and Ruby; Implementing Regular Expressions – series of articles by Russ Cox, author of RE2; Regular Expression Engines
Greed, in regular expression context, describes the number of characters which will be matched (often also stated as "consumed") by a variable length portion of a regular expression – a token or group followed by a quantifier, which specifies a number (or range of numbers) of tokens. If the portion of the regular expression is "greedy", it ...
A match is made, not when all the atoms of the string are matched, but rather when all the pattern atoms in the regex have matched. The idea is to make a small pattern of characters stand for a large number of possible strings, rather than compiling a large list of all the literal possibilities.
TRE is an open-source library for pattern matching in text, [2] which works like a regular expression engine with the ability to do approximate string matching. [3] It was developed by Ville Laurikari [1] and is distributed under a 2-clause BSD-like license.
In many programming languages, a particular syntax of strings is used to represent regular expressions, which are patterns describing string characters. However, it is possible to perform some string pattern matching within the same framework that has been discussed throughout this article.
A regex search scans the text of each page on Wikipedia in real time, character by character, to find pages that match a specific sequence or pattern of characters. Unlike keyword searching, regex searching is by default case-sensitive, does not ignore punctuation, and operates directly on the page source (MediaWiki markup) rather than on the ...
In computer science, an algorithm for matching wildcards (also known as globbing) is useful in comparing text strings that may contain wildcard syntax. [1] Common uses of these algorithms include command-line interfaces, e.g. the Bourne shell [2] or Microsoft Windows command-line [3] or text editor or file manager, as well as the interfaces for some search engines [4] and databases. [5]
Gestalt pattern matching, [1] also Ratcliff/Obershelp pattern recognition, [2] is a string-matching algorithm for determining the similarity of two strings. It was developed in 1983 by John W. Ratcliff and John A. Obershelp and published in the Dr. Dobb's Journal in July 1988.