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Generating Specialized Rules and Programs for Demand-Driven Analysis

  • K. Tuncay Tekle
  • Katia Hristova
  • Yanhong A. Liu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5140)

Abstract

Many complex analysis problems can be most clearly and easily specified as logic rules and queries, where rules specify how given facts can be combined to infer new facts, and queries select facts of interest to the analysis problem at hand. However, it has been extremely challenging to obtain efficient implementations from logic rules and to understand their time and space complexities, especially for on-demand analysis driven by queries.

This paper describes a powerful method for generating specialized rules and programs for demand-driven analysis from Datalog rules and queries, and further for providing time and space complexity guarantees. The method combines recursion conversion with specialization of rules and then uses a method for program generation and complexity calculation from rules. We compare carefully with the best prior methods by examining many variants of rules and queries for the same graph reachability problems, and show the application of our method in implementing graph query languages in general.

Keywords

Model Check Logic Programming Transitive Closure Partial Evaluation Logic Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • K. Tuncay Tekle
    • 1
  • Katia Hristova
    • 1
  • Yanhong A. Liu
    • 1
  1. 1.SUNY Stony BrookNYUSA

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