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Soot-based implementation of a demand-driven reaching definitions analysis

Published:14 June 2012Publication History

ABSTRACT

As a classical data-flow analysis, reaching definitions analysis is the corner stone of various techniques, such as code optimization and program slicing. The built-in data-flow analysis framework in Soot has been implemented in the traditional iterative style. While being able to meet general requirements for implementation of data flow analyses, the framework may be less efficient for a certain type of analyses in which the complete data-flow solution is unnecessary.

In this paper, we introduce our Soot-based implementation of an inter-procedural demand-driven reaching definitions analysis. For a demand for reaching definitions facts, the analysis only explores relevant program points and variables, saving a considerable amount of computation. Preliminary results show that the implementation can be much more efficient than its traditional counterpart in several scenarios. The Soot framework has greatly facilitated the implementation by providing abundant basic analysis results via well designed APIs.

References

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  2. E. Duesterwald. A demand-driven approach for efficient interprocedural data flow analysis. PhD thesis, Pittsburgh, PA, USA, 1996. AAI9727844. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. E. Duesterwald, R. Gupta, and M. L. Soffa. A practical framework for demand-driven interprocedural data flow analysis. ACM Trans. Program. Lang. Syst., 19(6):992--1030, Nov. 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. P. Lam, E. Bodden, O. Lhoták, and L. Hendren. The soot framework for java program analysis: a retrospective. In Cetus Users and Compiler Infrastructure Workshop, Galveston Island, TX, October 2011.Google ScholarGoogle Scholar
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        cover image ACM Conferences
        SOAP '12: Proceedings of the ACM SIGPLAN International Workshop on State of the Art in Java Program analysis
        June 2012
        58 pages
        ISBN:9781450314909
        DOI:10.1145/2259051

        Copyright © 2012 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 14 June 2012

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