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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 .
List of regular expression libraries Name Official website Programming language Software license Used by Boost.Regex [Note 1] Boost C++ Libraries: C++: Boost: Notepad++ >= 6.0.0, EmEditor: Boost.Xpressive Boost C++ Libraries: C++ Boost DEELX RegExLab: C++ Proprietary FREJ [Note 2] Fuzzy Regular Expressions for Java: Java: LGPL GLib/GRegex [Note ...
TRE allows specifying of cost for each of three typos type independently.. The project comes with a command-line utility, a reimplementation of agrep.. Though approximate matching requires some syntax extension, when this feature is not used, TRE works like most of other regular expression matching engines.
For function that manipulate strings, modern object-oriented languages, like C# and Java have immutable strings and return a copy (in newly allocated dynamic memory), while others, like C manipulate the original string unless the programmer copies data to a new string.
The specification of a programming language often includes a set of rules, the lexical grammar, which defines the lexical syntax. The lexical syntax is usually a regular language, with the grammar rules consisting of regular expressions; they define the set of possible character sequences (lexemes) of a token. A lexer recognizes strings, and ...
The RE2 algorithm has been rewritten in Rust as the package "regex". CloudFlare's web application firewall uses this package because the RE2 algorithm is immune to ReDoS. [8] Russ Cox also wrote RE1, an earlier regular expression based on a bytecode interpreter. [9] OpenResty uses a RE1 fork called "sregex". [10]
A string-searching algorithm, sometimes called string-matching algorithm, is an algorithm that searches a body of text for portions that match by pattern. A basic example of string searching is when the pattern and the searched text are arrays of elements of an alphabet ( finite set ) Σ.
Standard examples of data-driven languages are the text-processing languages sed and AWK, [1] and the document transformation language XSLT, where the data is a sequence of lines in an input stream – these are thus also known as line-oriented languages – and pattern matching is primarily done via regular expressions or line numbers.