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  2. Reference counting - Wikipedia

    en.wikipedia.org/wiki/Reference_counting

    The reference count of a string is checked before mutating a string. This allows reference count 1 strings to be mutated directly whilst higher reference count strings are copied before mutation. This allows the general behaviour of old style pascal strings to be preserved whilst eliminating the cost of copying the string on every assignment.

  3. Approximate string matching - Wikipedia

    en.wikipedia.org/wiki/Approximate_string_matching

    The closeness of a match is measured in terms of the number of primitive operations necessary to convert the string into an exact match. This number is called the edit distance between the string and the pattern. The usual primitive operations are: [1] insertion: cot → coat; deletion: coat → cot

  4. Comparison of programming languages (string functions)

    en.wikipedia.org/wiki/Comparison_of_programming...

    For function that manipulate strings, modern object-oriented languages, like C# and Java have immutable strings and return a copy (in newly allocated dynamic memory), while others, like C manipulate the original string unless the programmer copies data to a new string.

  5. Pattern matching - Wikipedia

    en.wikipedia.org/wiki/Pattern_matching

    Here, 0 is a single value pattern. Now, whenever f is given 0 as argument the pattern matches and the function returns 1. With any other argument, the matching and thus the function fail. As the syntax supports alternative patterns in function definitions, we can continue the definition extending it to take more generic arguments:

  6. Matching wildcards - Wikipedia

    en.wikipedia.org/wiki/Matching_wildcards

    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]

  7. Edit distance - Wikipedia

    en.wikipedia.org/wiki/Edit_distance

    Edit distance finds applications in computational biology and natural language processing, e.g. the correction of spelling mistakes or OCR errors, and approximate string matching, where the objective is to find matches for short strings in many longer texts, in situations where a small number of differences is to be expected.

  8. Regular expression - Wikipedia

    en.wikipedia.org/wiki/Regular_expression

    Matches the ending position of the string or the position just before a string-ending newline. In line-based tools, it matches the ending position of any line. Defines a marked subexpression, also called a capturing group, which is essential for extracting the desired part of the text (See also the next entry, \ n ).

  9. Nesting (computing) - Wikipedia

    en.wikipedia.org/wiki/Nesting_(computing)

    In a spreadsheet functions can be nested one into another, making complex formulas. The function wizard of the OpenOffice.org Calc application allows to navigate through multiple levels of nesting, [further explanation needed] letting the user to edit (and possibly correct) each one of them separately. For example: =IF(SUM(C8:G8)=0,"Y","N")