Multi-Core LTSmin: Marrying Modularity and Scalability

  • Alfons Laarman
  • Jaco van de Pol
  • Michael Weber
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6617)


The LTSmin toolset provides multiple generation and on-the-fly analysis algorithms for large graphs (state spaces), typically generated from concise behavioral specifications (models) of systems. LTSmin supports a variety of input languages, but its key feature is modularity: language frontends, optimization layers, and algorithmic backends are completely decoupled, without sacrificing performance. To complement our existing symbolic and distributed model checking algorithms, we added a multi-core backend for checking safety properties, with several new features to improve efficiency and memory usage: low-overhead load balancing, incremental hashing and scalable state compression.


Model Check Hash Table Memory Usage Reachability Analysis Input Language 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Barnat, J., Ročkai, P.: Shared hash tables in parallel model checking. Elec. Notes in Theor. Comp. Sc. 198(1), 79–91 (2008); Proc. of the 6th International Workshop on Parallel and Distributed Methods in verifiCation (PDMC 2007)CrossRefGoogle Scholar
  2. 2.
    Blom, S., van de Pol, J., Weber, M.: Bridging the gap between enumerative and symbolic model checkers. Tech. Rep. TR-CTIT-09-30, Centre for Telematics and Information Technology, University of Twente, Enschede (2009)Google Scholar
  3. 3.
    Blom, S., Lisser, B., van de Pol, J., Weber, M.: A database approach to distributed state space generation. In: Sixth Intl. Workshop on Par. and Distr. Methods in verifiCation, PDMC, pp. 17–32. CTIT, Enschede (2007)Google Scholar
  4. 4.
    Blom, S., van de Pol, J., Weber, M.: LTSmin: Distributed and symbolic reachability. In: Touili, T., Cook, B., Jackson, P. (eds.) CAV 2010. LNCS, vol. 6174, pp. 354–359. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  5. 5.
    Holzmann, G.J., Bošnacki, D.: The design of a multicore extension of the SPIN model checker. IEEE Trans. Softw. Eng. 33(10), 659–674 (2007)CrossRefGoogle Scholar
  6. 6.
    Laarman, A.W., van de Pol, J.C., Weber, M.: Boosting multi-core reachability performance with shared hash tables. In: Sharygina, N., Bloem, R. (eds.) Proceedings of the 10th International Conference on Formal Methods in Computer-Aided Design, Lugano, Swiss. IEEE Computer Society, USA (2010)Google Scholar
  7. 7.
    Nguyen, V.Y., Ruys, T.C.: Incremental hashing for spin. In: Havelund, K., Majumdar, R., Palsberg, J. (eds.) SPIN 2008. LNCS, vol. 5156, pp. 232–249. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  8. 8.
    Pelánek, R.: BEEM: Benchmarks for explicit model checkers. In: Bošnački, D., Edelkamp, S. (eds.) SPIN 2007. LNCS, vol. 4595, pp. 263–267. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  9. 9.
    Sanders, P.: Load Balancing Algorithms for Parallel Depth First Search. Ph.D. thesis, University of Karlsruhe (1997)Google Scholar
  10. 10.
    Zobrist, A.L.: A new hashing method with application for game playing. Tech. Rep. 88, Computer Sciences Department, University of Wisconsin (1969)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Alfons Laarman
    • 1
  • Jaco van de Pol
    • 1
  • Michael Weber
    • 1
  1. 1.Formal Methods and ToolsUniversity of TwenteThe Netherlands

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