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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]
var x1 = 0; // A global variable, because it is not in any function let x2 = 0; // Also global, this time because it is not in any block function f {var z = 'foxes', r = 'birds'; // 2 local variables m = 'fish'; // global, because it wasn't declared anywhere before function child {var r = 'monkeys'; // This variable is local and does not affect the "birds" r of the parent function. z ...
A word input can be put in double "quotes" to turn off stemming. A phrase input can use greyspace to turn on stemming. A single word input can suffix the tilde ~ character for a fuzzy search. A single word input can suffix the star * character for a wildcard search. Intitle does not search redirects. Proximity search is not an option in a title ...
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.
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.
A basic search string is simply the topic you are interested in reading about. A direct match of a basic search string will navigate you directly to Wikipedia's article that has that title. A non-match, or any other type of search string will take you to Wikipedia's search results page, where the results of your search are displayed.
Pattern matching programming languages (2 C, 30 P) R. Regular expressions (1 C, 12 P) S. String matching algorithms (1 C, 16 P) Pages in category "Pattern matching"
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 lengths. To find multiple matches, the expected time is linear in the input lengths, plus the combined length of all the matches, which could ...