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RE/flex supports Unicode regular expression patterns in lexer specifications and automatically tokenizes UTF-8, UTF-16, and UTF-32 input files. Code pages may be specified to tokenize input files encoded in ISO/IEC 8859 1 to 16, Windows-1250 to Windows-1258, CP-437, CP-850, CP-858, MacRoman, KOI-8, EBCDIC, and so on. Normalization to UTF-8 is ...
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 .
The patterns generally have the form of either sequences or tree structures. Uses of pattern matching include outputting the locations (if any) of a pattern within a token sequence, to output some component of the matched pattern, and to substitute the matching pattern with some other token sequence (i.e., search and replace).
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]
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 simple and inefficient way to see where one string occurs inside another is to check at each index, one by one. First, we see if there is a copy of the needle starting at the first character of the haystack; if not, we look to see if there's a copy of the needle starting at the second character of the haystack, and so forth.
In computer science, the Krauss wildcard-matching algorithm is a pattern matching algorithm. Based on the wildcard syntax in common use, e.g. in the Microsoft Windows command-line interface, the algorithm provides a non-recursive mechanism for matching patterns in software applications, based on syntax simpler than that typically offered by regular expressions.
Then, the number of states of A is 2s − c (linear in the size of E). The number of transitions leaving any state is at most two. Since an NFA of m states and at most e transitions from each state can match a string of length n in time O(emn), a Thompson NFA can do pattern matching in linear time, assuming a fixed-size alphabet. [4] [better ...