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Parallel Graph-Based Stateless Model Checking

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Automated Technology for Verification and Analysis (ATVA 2020)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12302))

Abstract

Stateless model checking (SMC) is an automatic technique with low memory requirements for finding errors in concurrent programs or for checking for their absence. To be effective, SMC tools require algorithms that combat the combinatorial explosion in the number of process/thread interactions that need to be explored. In recent years, a plethora of such algorithms have emerged, which can be classified broadly in those that explore interleavings (i.e., complete serializations of events) and those that explore traces (i.e., graphs of events). In either case, an SMC algorithm is optimal if it explores exactly one representative from each class of equivalent executions. In this paper, we examine the parallelization of a state-of-the-art graph-based algorithm for SMC under sequential consistency, based on the reads-from relation. The algorithm is provably optimal, and in practice spends only polynomial time per equivalence class. We present the modifications to the algorithm that its parallelization requires and implementation aspects that allow us to make it scalable. We report on the performance and scalability that we were able to achieve on C/pthread programs, and how this performance compares to that of other SMC tools. Finally, we argue for the inherent advantages that graph-based algorithms have over interleaving-based ones for achieving scalability when parallelism enters the picture.

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Notes

  1. 1.

    In Table 1, entries signify that the tool cannot handle that program; a symbol that the benchmark does not complete after running for more than ten hours. The circular-buffer program contains a concurrency error which only manifests itself for parameter values \(\ge 10\). The CDSChecker tool finds this error immediately (within the first few executions), hence the symbols for its circular-buffer(10) entries. The remaining three tools are not so lucky in their search, and catch the error after exploring many executions. The parallel version of Nidhugg/rfsc detects this error at a point that is influenced by the distribution of tasks to threads, which also explains the slight variation in the curve of circular-buffer(10) in Fig. 4.

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Acknowledgments

We would like to acknowledge the work of Nodari Kankava and Alexis Remmers for an initial prototype implementation of the algorithm which formed the basis for Par-RF-SMC ’s implementation in Nidhugg. This work has been partially supported by the Swedish Research Council through grant #621-2017-04812, and by the Swedish Foundation for Strategic Research through the aSSIsT project.

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  1. Department of Information Technology, Uppsala University, Uppsala, Sweden

    Magnus Lång & Konstantinos Sagonas

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  1. Magnus Lång
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Correspondence to Magnus Lång .

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  1. Vietnam National University (VNU-UET), Hanoi, Vietnam

    Dang Van Hung

  2. University of Pennsylvania, Philadelphia, PA, USA

    Oleg Sokolsky

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Lång, M., Sagonas, K. (2020). Parallel Graph-Based Stateless Model Checking. In: Hung, D.V., Sokolsky, O. (eds) Automated Technology for Verification and Analysis. ATVA 2020. Lecture Notes in Computer Science(), vol 12302. Springer, Cham. https://doi.org/10.1007/978-3-030-59152-6_21

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  • DOI: https://doi.org/10.1007/978-3-030-59152-6_21

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