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Generating language-based environments / Thomas W. Reps.

By: Reps, Thomas W., (Thomas William) [author.].
Contributor(s): IEEE Xplore (Online Service) [distributor.] | MIT Press [publisher.].
Material type: materialTypeLabelBookSeries: Acm doctoral dissertation award: Publisher: Cambridge, Massachusetts : MIT Press, c1984Distributor: [Piscataqay, New Jersey] : IEEE Xplore, [2004]Description: 1 PDF (138 pages) : illustrations.Content type: text Media type: electronic Carrier type: online resourceISBN: 0262181150; 9780262256858.Subject(s): Computer programming | Interactive computer systems | Text editors (Computer programs) | Programming languages (Electronic computers) -- SemanticsGenre/Form: Electronic books.Additional physical formats: Print version: No titleDDC classification: 001.64/2 Online resources: Abstract with links to resource Also available in print.Dissertation note: Originally presented as the author's thesis (Ph. D.)--Cornell University, 1983. Summary: This book addresses a fundamental software engineering issue, applying formal techniques and rigorous analysis to a practical problem of great current interest: the incorporation of language-specific knowledge in interactive programming environments. It makes a basic contribution in this area by proposing an attribute-grammar framework for incremental semantic analysis and establishing its algorithmic foundations. The results are theoretically important while having immediate practical utility for implementing environment-generating systems.The book's principal technical results include: an optimal-time algorithm to incrementally maintain a consistent attributed-tree of attribute grammar subclasses, allowing an optimizing environment-generator to select the most efficient applicable algorithm; a general method for sharing storage among attributes whose values are complex data structures; and two algorithms that carry out attribute evaluation while reducing the number of intermediate attribute values retained. While others have worked on this last problem, Reps's algorithms are the first to achieve sublinear worst-case behavior. One algorithm is optimal, achieving the log n lower space bound in nonlinear time, while the second algorithm uses as much as root n. space but runs in linear time.
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