Search results
Results from the WOW.Com Content Network
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 ...
A very simple case of a regular expression in this syntax is to locate a word spelled two different ways in a text editor, the regular expression seriali[sz]e matches both "serialise" and "serialize". Wildcard characters also achieve this, but are more limited in what they can pattern, as they have fewer metacharacters and a simple language-base.
RE2 is a software library which implements a regular expression engine. It uses finite-state machines, in contrast to most other regular expression libraries. RE2 supports a C++ interface. RE2 was implemented by Google and Google uses RE2 for Google products. [3]
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.
Raku rules are the regular expression, string matching and general-purpose parsing facility of the Raku programming language, and are a core part of the language. Since Perl's pattern-matching constructs have exceeded the capabilities of formal regular expressions for some time, Raku documentation refers to them exclusively as regexes, distancing the term from the formal definition.
Regular languages are a category of languages (sometimes termed Chomsky Type 3) which can be matched by a state machine (more specifically, by a deterministic finite automaton or a nondeterministic finite automaton) constructed from a regular expression. In particular, a regular language can match constructs like "A follows B", "Either A or B ...
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
In information theory, the Hamming distance between two strings or vectors of equal length is the number of positions at which the corresponding symbols are different. In other words, it measures the minimum number of substitutions required to change one string into the other, or equivalently, the minimum number of errors that could have transformed one string into the other.