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A practical framework for demand-driven interprocedural data flow analysis

Editor: William Pugh Authors:

Evelyn Duesterwald,

Mary Lou SoffaAuthors Info & Claims

ACM Transactions on Programming Languages and Systems (TOPLAS), Volume 19, Issue 6

Pages 992 - 1030

https://doi.org/10.1145/267959.269970

Published: 01 November 1997 Publication History

Abstract

The high cost and growing importance of interprocedural data flow analysis have led to an increased interest in demand-driven algorithms. In this article, we present a general framework for developing demand-driven interprocedural data flow analyzers and report our experience in evaluating the performance of this approach. A demand for data flow information is modeled as a set of queries. The framework includes a generic demand-driven algorithm that determines the response to query by iteratively applying a system of query propagation rules. The propagation rules yield precise responses for the class of distributive finite data flow problems. We also describe a two-phase framework variation to accurately handle nondistributive problems. A performance evaluation of our demand-driven approach is presented for two data flow problems, namely, reaching-definitions and copy constant propagation. Our experiments show that demand-driven analysis performs well in practice, reducing both time and space requirements when compared with exhaustive analysis.

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Index Terms

A practical framework for demand-driven interprocedural data flow analysis
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Question answering
2. Software and its engineering
  1. Software creation and management
    1. Designing software
      1. Software implementation planning
        Software design techniques
    2. Software development process management
  2. Software notations and tools
    1. Compilers

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Published In

cover image ACM Transactions on Programming Languages and Systems

ACM Transactions on Programming Languages and Systems Volume 19, Issue 6

Nov. 1997

235 pages

ISSN:0164-0925

EISSN:1558-4593

DOI:10.1145/267959

Editor:
William Pugh
Univ. of Maryland, College Park

Issue’s Table of Contents

Copyright © 1997 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 November 1997

Published in TOPLAS Volume 19, Issue 6

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HajiHosseinKhani SLashkari AMizani Oskui A(2023)Unveiling Vulnerable Smart Contracts: Toward Profiling Vulnerable Smart Contracts using Genetic Algorithm and Generating Benchmark DatasetBlockchain: Research and Applications10.1016/j.bcra.2023.100171(100171)Online publication date: Nov-2023
https://doi.org/10.1016/j.bcra.2023.100171
Jaiswal SKhedker UChakraborty S(2020)Bidirectionality in flow-sensitive demand-driven analysisScience of Computer Programming10.1016/j.scico.2020.102391(102391)Online publication date: Jan-2020
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Fachinetti LPalmer ZSmith SWu KYorihiro A(2020)A Set-Based Context Model for Program AnalysisProgramming Languages and Systems10.1007/978-3-030-64437-6_1(3-24)Online publication date: 30-Nov-2020
https://dl.acm.org/doi/10.1007/978-3-030-64437-6_1
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Facchinetti LPalmer ZSmith S(2019)Higher-order Demand-driven Program AnalysisACM Transactions on Programming Languages and Systems10.1145/331034041:3(1-53)Online publication date: 2-Jul-2019
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