Parsing Techniques: A Practical Guide, Second Edition | Date: 06 May 2011, 20:08
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* Accessible, yet comprehensive introduction to parsing techniques helps readers to quickly gain a broad understanding of subject
* Summarizes more than 700 papers referenced in the book, saving readers countless hours
* Many exercises include hints and partial solutions, making it ideal for self-study or classroom use
* Extensive bibliography, as well as annotated bibliography on the website, to help interested readers to find more information
Parsing, also referred to as syntax analysis, has been and continues to be an essential part of computer science and linguistics. Today, parsing is also applied in other disciplines; some examples are document preparation and conversion, chemical formulae typesetting, and chromosome recognition.
In addition to the traditional parsing techniques, this second edition presents new developments and discoveries: generalized deterministic parsing, linear-time substring parsing, parallel parsing, parsing as intersection, non-canonical methods, non-Chomsky systems, and many more.
Parsing techniques provide a solid basis for compiler construction and linguistics, and contribute to all existing software: they enable Web browsers to analyze HTML pages and PostScript printers to analyze PostScript, and some of the more advanced techniques are used in code generation in compilers and in data compression. Also their importance as general pattern recognizers is slowly being acknowledged.
To provide readers with low-threshold access to the full field of parsing techniques, this book uses a two-tiered structure. The basic ideas behind the existing parsing techniques are explained in an intuitive and narrative style, starting from the first principles of data structures and algorithms; this provides breadth and accessibility. The hundreds of realizations and improvements of these basic ideas are explained in an extensive annotated bibliography, in a much terser, yet still informal style; this provides depth.
The reader should have an understanding of algorithmic thinking, especially recursion; however, knowledge of any particular programming language is not required.
Written for:
Researchers, recreational mathematicians, and advanced graduate students.
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