Static analysis for concurrent programs with applications to data race detection

Vineet Kahlon, Sriram Sankaranarayanan, Aarti Gupta

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


We propose a general framework for static analysis of concurrent multi-threaded programs in the presence of various types of synchronization primitives such as locks and pairwise rendezvous. In order to capture interference between threads, we use the notion of a transaction, i.e., a sequence of statements in a thread that can be executed atomically, without sacrificing the soundness of the analysis while yielding precise results. These transactions are delineated automatically, and are captured in the form of a transaction graph over the global control state space of the program. Starting from a coarse transaction graph, constructed by exploiting scheduling constraints related to synchronizations and partial order reduction, we iteratively refine the graph by removing statically unreachable nodes using the results of various analyses. Specifically, we use abstract interpretation to automatically derive program invariants, based on abstract domains of increasing precision. Progressive refinement of the transaction graph enhances scalability of the static analyses, yielding more precise invariants. We demonstrate the benefits of this framework in an application to find data race bugs in concurrent programs, where our static analyses serve to reduce the number of false warnings captured by an initial lockset analysis. This framework also facilitates use of model checking on the remaining warnings to generate concrete error traces, where we leverage the preceding static analyses to generate small program slices and the derived invariants to improve performance. We describe our experimental results on a suite of Linux device drivers.

Original languageEnglish (US)
Pages (from-to)321-336
Number of pages16
JournalInternational Journal on Software Tools for Technology Transfer
Issue number4
StatePublished - Aug 2013

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems


  • Abstract interpretation
  • Data race detection
  • Multi-threaded programs
  • Static analysis
  • Transaction graphs


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