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Besides the built-in RE/flex POSIX regex pattern matcher, RE/flex also supports PCRE2, Boost.Regex and std::regex pattern matching libraries. PCRE2 and Boost.Regex offer a richer regular expression pattern syntax with Perl pattern matching semantics, but are slower due to their intrinsic NFA-based matching algorithm.
A pattern is a string of characters intended to match one or more user inputs. A literal pattern like WHAT IS YOUR NAME will match only one input, ignoring case: "what is your name". But patterns may also contain wildcards, which match one or more words. A pattern like WHAT IS YOUR *
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.
If the characters do not match, there is no need to continue searching backwards along the text. If the character in the text does not match any of the characters in the pattern, then the next character in the text to check is located m characters farther along the text, where m is the length of the pattern.
It combines ideas from Aho–Corasick with the fast matching of the Boyer–Moore string-search algorithm. For a text of length n and maximum pattern length of m, its worst-case running time is O(mn), though the average case is often much better. [2] GNU grep once implemented a string matching algorithm very similar to Commentz-Walter. [3]
The simplest pattern in pattern matching is an explicit value or a variable. For an example, consider a simple function definition in Haskell syntax (function parameters are not in parentheses but are separated by spaces, = is not assignment but definition):
In computer science, the Knuth–Morris–Pratt algorithm (or KMP algorithm) is a string-searching algorithm that searches for occurrences of a "word" W within a main "text string" S by employing the observation that when a mismatch occurs, the word itself embodies sufficient information to determine where the next match could begin, thus bypassing re-examination of previously matched characters.
The best case is the same as for the Boyer–Moore string-search algorithm in big O notation, although the constant overhead of initialization and for each loop is less. The worst case behavior happens when the bad character skip is consistently low (with the lower limit of 1 byte movement) and a large portion of the needle matches the haystack.