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Model Checking B Models via High-Level Code Generation

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Formal Methods and Software Engineering (ICFEM 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13478))

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Abstract

We present a new approach to improve the model checking performance for B models. We build on the high-level code generator B2Program, which unlike B’s original code generators can already be applied at an early stage to high-level B models. We extend B2Program to generate efficient model checkers in Java and C++. The generated model checkers are customized and compiled for specific B models and include features like parallelization and caching. We evaluate the approach on a wide range of B models, comparing the performance to existing B model checkers. The results show that for some models we can obtain significant performance improvements, while for others ProB remains the tool of choice. For lower-level models, our new approach improves upon the existing TLC backend. In summary, the B2Program model checker is a very useful new tool addition for the B method.

The works of Fabian Vu and Michael Leuschel are part of the IVOIRE project, which is funded by “Deutsche Forschungsgemeinschaft” (DFG) and the Austrian Science Fund (FWF) grant # I 4744-N.

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Notes

  1. 1.

    Available at: https://github.com/favu100/b2program.

  2. 2.

    In the absence of the WHILE loop, such a rewriting is always possible (cf. the normal form for substitutions in Chap. 6 of [1]).

  3. 3.

    Note that top-level preconditions are treated as similar to guards, and we only allow top-level guards and preconditions as non-determinism.

  4. 4.

    Note that TLC also has problems when the number of variables of a model increases, in terms of stack consumption and runtime degradation.

  5. 5.

    64-Bit Server VM (build 15+36-1562, mixed mode, sharing).

  6. 6.

    Apple clang version 13.0.0 (clang-1300.0.29.30).

  7. 7.

    Revision b6d1b600dbf06b7984dd2a1dd7403206cfd9d394.

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Acknowledgements

We would like to thank Florian Mager and Klaus Sausen. They have been working on a student’s model checking project from which some ideas have emerged for this work. We would also like to thank Lucas Döring, who is currently improving B2Program’s model checking performance. We would also like to thank Sebastian Stock for proofreading this paper and anonymous referees for their feedback.

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Authors and Affiliations

  1. Institut für Informatik, Universität Düsseldorf, Universitätsstr. 1, 40225, Düsseldorf, Germany

    Fabian Vu, Dominik Brandt & Michael Leuschel

Authors
  1. Fabian Vu
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  2. Dominik Brandt
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  3. Michael Leuschel
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Corresponding author

Correspondence to Fabian Vu .

Editor information

Editors and Affiliations

  1. Complutense University of Madrid, Madrid, Spain

    Adrian Riesco

  2. East China University of Science and Technology, Shanghai, China

    Min Zhang

A Benchmarks

A Benchmarks

Table 2. Single-threaded runtimes of ProB, TLC, and generated code in Java, and C++ (Compiled with -O1) in seconds with state space size, speed-up relative to ProB, memory usage in KB, OP = Operation Reuse, ST = Standard, C = Caching
Full size table
Table 3. Multi-threaded (6 Threads) runtimes of TLC, and generated code in Java, and C++ (Compiled with -O1) in seconds with state space size, speed-up relative to TLC and relative to single-threaded, memory usage in KB, TH = Thread, ST = Standard, C = Caching
Full size table

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Vu, F., Brandt, D., Leuschel, M. (2022). Model Checking B Models via High-Level Code Generation. In: Riesco, A., Zhang, M. (eds) Formal Methods and Software Engineering. ICFEM 2022. Lecture Notes in Computer Science, vol 13478. Springer, Cham. https://doi.org/10.1007/978-3-031-17244-1_20

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  • DOI: https://doi.org/10.1007/978-3-031-17244-1_20

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