Parsing Techniques: A Practical Guide (Monographs in Computer Science) [Englisch] [Gebundene Ausgabe]

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.

Parsing - syntax analysis by computer - has been and continues to be an essential part of computer science. Parsing techniques have provided a solid basis for compiler construction since the mid-1960s, and continue to do so, thereby contributing to all existing software today. They enable Web browsers to analyze HTML pages, and PostScript printers to analyze PostScript, among other things; and some of the more advanced techniques are being used in code generation in compilers and in data compression. In linguistics, the importance of formal grammars was recognized early on, but only relatively recently have the corresponding parsing techniques been applied extensively; and their importance as general pattern recognizers is slowly being acknowledged. Today, with problems of speed and memory largely out of the way, these general techniques have grown considerably in importance, both in computer science, where advanced compilers now often use general CF parsers, and in 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. To provide readers with low-threshold access to the full field of parsing techniques, this second edition uses a two-tiered structure. The basic ideas behind the dozen or so existing parsing techniques are explained in an intuitive and narrative style, starting from first principles of data structures and algorithms; this provides breadth and accessibility. The hundreds of realizations and improvements of these techniques are then explained in a much terser, yet still informal, style in the summaries of more than 700 papers referenced in the book; this provides depth.

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.