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Java Excel API (a.k.a. JXL API) ... Example Sample code to write to an Excel file might look like as follows: ... (String strSheetName, int iColumnNumber, int ...
Wildcard The wildcard . matches any character. For example, a.b matches any string that contains an "a", and then any character and then "b". a.*b matches any string that contains an "a", and then the character "b" at some later point.
The wildcard pattern (often written as _) is also simple: like a variable name, it matches any value, but does not bind the value to any name. Algorithms for matching wildcards in simple string-matching situations have been developed in a number of recursive and non-recursive varieties. [11]
A bounded wildcard is one with either an upper or a lower inheritance constraint. The bound of a wildcard can be either a class type, interface type, array type, or type variable. Upper bounds are expressed using the extends keyword and lower bounds using the super keyword. Wildcards can state either an upper bound or a lower bound, but not both.
The set ret can be saved efficiently by just storing the index i, which is the last character of the longest common substring (of size z) instead of S[(i-z+1)..i]. Thus all the longest common substrings would be, for each i in ret, S[(ret[i]-z)..(ret[i])]. The following tricks can be used to reduce the memory usage of an implementation:
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]
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 example of string searching is when the pattern and the searched text are arrays of elements of an alphabet Σ. Σ may be a human language alphabet, for example, the letters A through Z and other applications may use a binary alphabet (Σ = {0,1}) or a DNA alphabet (Σ = {A,C,G,T}) in bioinformatics.