Search results
Results From The WOW.Com Content Network
Regular expressions are used in search engines, in search and replace dialogs of word processors and text editors, in text processing utilities such as sed and AWK, and in lexical analysis. Regular expressions are supported in many programming languages. Library implementations are often called an "engine", [4] [5] and many of these are ...
Most programming languages that have a string datatype will have some string functions although there may be other low-level ways within each language to handle strings directly. In object-oriented languages, string functions are often implemented as properties and methods of string objects.
In computer science, Thompson's construction algorithm, also called the McNaughton–Yamada–Thompson algorithm, [1] is a method of transforming a regular expression into an equivalent nondeterministic finite automaton (NFA). [2] This NFA can be used to match strings against the regular expression.
The original Mozilla proxy auto-config implementation, which provides a glob-matching function on strings, uses a replace-as-RegExp implementation as above. The bracket syntax happens to be covered by regex in such an example. Python's fnmatch uses a more elaborate procedure to transform the pattern into a regular expression. [17]
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 string literal or anonymous string is a literal for a string value in the source code of a computer program. Modern programming languages commonly use a quoted sequence of characters, formally "bracketed delimiters", as in x = "foo" , where , "foo" is a string literal with value foo .
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.
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.