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Relevance heuristics for program analysis

Published:07 January 2008Publication History

ABSTRACT

Relevance heuristics allow us to tailor a program analysis to a particular property to be verified. This in turn makes it possible to improve the precision of the analysis where needed, while maintaining scalability. In this talk I will discuss the principles by which SAT solvers and other decision procedures decide what information is relevant to a given proof. Then we will see how these ideas can be exploited in program verification using the method of Craig interpolation. The result is an analysis that is finely tuned to prove a given property of a program. At the end of the talk, I will cover some recent research in this area, including the use of interpolants for verifying heap-manipulating programs.

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  1. Relevance heuristics for program analysis

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      • Published in

        cover image ACM Conferences
        POPL '08: Proceedings of the 35th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
        January 2008
        448 pages
        ISBN:9781595936899
        DOI:10.1145/1328438
        • cover image ACM SIGPLAN Notices
          ACM SIGPLAN Notices  Volume 43, Issue 1
          POPL '08
          January 2008
          420 pages
          ISSN:0362-1340
          EISSN:1558-1160
          DOI:10.1145/1328897
          Issue’s Table of Contents

        Copyright © 2008 ACM

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        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 7 January 2008

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        Overall Acceptance Rate824of4,130submissions,20%

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