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In computer science, pattern matching is the act of checking a given sequence of tokens for the presence of the constituents of some pattern. In contrast to pattern recognition , the match usually has to be exact: "either it will or will not be a match."
Gestalt pattern matching, [1] also Ratcliff/Obershelp pattern recognition, [2] is a string-matching algorithm for determining the similarity of two strings. It was developed in 1983 by John W. Ratcliff and John A. Obershelp and published in the Dr. Dobb's Journal in July 1988.
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Generalizations of the same idea can be used to find more than one match of a single pattern, or to find matches for more than one pattern. To find a single match of a single pattern, the expected time of the algorithm is linear in the combined length of the pattern and text, although its worst-case time complexity is the product of the two ...
Common applications of approximate matching include spell checking. [5] With the availability of large amounts of DNA data, matching of nucleotide sequences has become an important application. [1] Approximate matching is also used in spam filtering. [5] Record linkage is a common application where records from two disparate databases are matched.
The second, or default case x -> 1 matches the pattern x against the argument and returns 1. This case is used only if the matching failed in the first case. The first, or special case matches against any compound, such as a non-empty list, or pair. Matching binds x to the left component and y to the right component. Then the body of the case ...
They are easy to define and easy to use, largely because of pattern matching, and most Standard ML implementations' pattern-exhaustiveness checking and pattern redundancy checking. In object-oriented programming languages, a disjoint union can be expressed as class hierarchies. However, in contrast to class hierarchies, ADTs are closed. Thus ...