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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 ...
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 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 .
Tree patterns are used in some programming languages as a general tool to process data based on its structure, e.g. C#, [1] F#, [2] Haskell, [3] Java [4], ML, Python, [5] Ruby, [6] Rust, [7] Scala, [8] Swift [9] and the symbolic mathematics language Mathematica have special syntax for expressing tree patterns and a language construct for ...
A parsing expression is a kind of pattern that each string may either match or not match.In case of a match, there is a unique prefix of the string (which may be the whole string, the empty string, or something in between) which has been consumed by the parsing expression; this prefix is what one would usually think of as having matched the expression.
Computing E(m, j) is very similar to computing the edit distance between two strings. In fact, we can use the Levenshtein distance computing algorithm for E ( m , j ), the only difference being that we must initialize the first row with zeros, and save the path of computation, that is, whether we used E ( i − 1, j ), E( i , j − 1) or E ( i ...
The difference between the two algorithms consists in that the optimal string alignment algorithm computes the number of edit operations needed to make the strings equal under the condition that no substring is edited more than once, whereas the second one presents no such restriction.