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Regular Expression Flavor Comparison – Detailed comparison of the most popular regular expression flavors; Regexp Syntax Summary; Online Regular Expression Testing – with support for Java, JavaScript, .Net, PHP, Python and Ruby; Implementing Regular Expressions – series of articles by Russ Cox, author of RE2; Regular Expression Engines
A parsing expression is a kind of pattern that each string may either match or not match.In case of a match, there is a unique prefix of the string (which may be the whole string, the empty string, or something in between) which has been consumed by the parsing expression; this prefix is what one would usually think of as having matched the expression.
In computer science, an operator-precedence parser is a bottom-up parser that interprets an operator-precedence grammar. For example, most calculators use operator-precedence parsers to convert from the human-readable infix notation relying on order of operations to a format that is optimized for evaluation such as Reverse Polish notation (RPN).
Every regular expression can be written solely in terms of the Kleene star and set unions over finite words. This is a surprisingly difficult problem. As simple as the regular expressions are, there is no method to systematically rewrite them to some normal form. The lack of axiom in the past led to the star height problem.
A predictive parser is a recursive descent parser that does not require backtracking. [3] Predictive parsing is possible only for the class of LL( k ) grammars, which are the context-free grammars for which there exists some positive integer k that allows a recursive descent parser to decide which production to use by examining only the next k ...
While useful, pure parser generators only address the parsing part of the problem of building a compiler. Tools with broader scope, such as PQCC, Coco/R and DMS Software Reengineering Toolkit provide considerable support for more difficult post-parsing activities such as semantic analysis, code optimization and generation.
Around the 1970s/1980s the term information engineering methodology (IEM) was created to describe database design and the use of software for data analysis and processing. [3] [4] These techniques were intended to be used by database administrators (DBAs) and by systems analysts based upon an understanding of the operational processing needs of organizations for the 1980s.
The algorithm, named after its inventor, Jay Earley, is a chart parser that uses dynamic programming; it is mainly used for parsing in computational linguistics. It was first introduced in his dissertation [ 2 ] in 1968 (and later appeared in an abbreviated, more legible, form in a journal [ 3 ] ).