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Parsing Techniques: A Practical Guide (Monographs in Computer Science)
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About Parsing Techniques: A Practical Guide
Product Description This second edition of Grune and Jacobs’ brilliant work presents new developments and discoveries that have been made in the field. Parsing, also referred to as syntax analysis, has been and continues to be an essential part of computer science and linguistics. Parsing techniques have grown considerably in importance, both in computer science, ie. advanced compilers often use general CF parsers, and computational linguistics where such parsers are the only option. They are used in a variety of software products including Web browsers, interpreters in computer devices, and data compression programs; and they are used extensively in linguistics. From the Back Cover 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.
