DUET: Static analysis for unbounded parallelism

Azadeh Farzan, Zachary Kincaid

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

DUET is a static analysis tool for concurrent programs in which the number of executing threads is not statically bounded. DUET has a modular architecture, which is based on separating the invariant synthesis problem in two subtasks: (1) data dependence analysis, which is used to construct a data flow model of the program, and (2) interpretation of the data flow model over a (possibly infinite) abstract domain, which generates invariants. This separation of concerns allows researchers working on data dependence analysis and abstract domains to combine their efforts toward solving the challenging problem of static analysis for unbounded concurrency. In this paper, we discuss the architecture of DUET as well as two data dependence analyses that have been implemented in the tool.

Original languageEnglish (US)
Title of host publicationComputer Aided Verification - 25th International Conference, CAV 2013, Proceedings
Pages191-196
Number of pages6
DOIs
StatePublished - Aug 12 2013
Externally publishedYes
Event25th International Conference on Computer Aided Verification, CAV 2013 - Saint Petersburg, Russian Federation
Duration: Jul 13 2013Jul 19 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8044 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other25th International Conference on Computer Aided Verification, CAV 2013
CountryRussian Federation
CitySaint Petersburg
Period7/13/137/19/13

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Farzan, A., & Kincaid, Z. (2013). DUET: Static analysis for unbounded parallelism. In Computer Aided Verification - 25th International Conference, CAV 2013, Proceedings (pp. 191-196). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8044 LNCS). https://doi.org/10.1007/978-3-642-39799-8_12