skip to main content
10.1145/2591062.2591088acmconferencesArticle/Chapter ViewAbstractPublication PagesicseConference Proceedingsconference-collections
Article

Formal verification problems in a big data world: towards a mighty synergy

Published:31 May 2014Publication History

ABSTRACT

Formal verification requires high performance data processing software for extracting knowledge from the unprecedented amount of data coming from analyzed systems. Since cloud based computing resources have became easily accessible, there is an opportunity for verification techniques and tools to undergo a deep technological transition to exploit the new available architectures. This has created an increasing interest in parallelizing and distributing verification techniques. In this paper we introduce a distributed approach which exploits techniques typically used by the bigdata community to enable verification of very complex systems using bigdata approaches and cloud computing facilities.

References

  1. Amazon Web Services. Elastic MapReduce. http:// aws.amazon.com/documentation/elasticmapreduce/, 2013. Last visited: June 2013.Google ScholarGoogle Scholar
  2. J. Barnat, L. Brim, and J. Chaloupka. Parallel breadth-first search ltl model-checking. In Automated Software Engineering, 2003. Proceedings. 18th IEEE International Conference on, pages 106–115, 2003.Google ScholarGoogle ScholarCross RefCross Ref
  3. J. Barnat, L. Brim, and I. ˘ Cerná. Property driven distribution of nested dfs. In M. Leuschel and U. Ultes-Nitsche (Eds.): Proceedings of the 3rd International Workshop on Verification and Computational Logic, pages 1–10, Pittsburgh, PA, USA, 2002. Dept. of Electronics and Computer Science, University of Southampton.Google ScholarGoogle Scholar
  4. J. Barnat, L. Brim, M. ˇ Ceˇ ska, and P. Roˇ ckai. Divine: Parallel distributed model checker. In Parallel and Distributed Methods in Verification, 2010 Ninth International Workshop on, and High Performance Computational Systems Biology, Second International Workshop on, pages 4–7, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. A. Bell and B. R. Haverkort. Sequential and distributed model checking of petri nets. International Journal on Software Tools for Technology Transfer, 7(1):43–60, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. C. Bellettini, M. Camilli, L. Capra, and M. Monga. Symbolic state space exploration of RT systems in the cloud. In Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2012, pages 295–302, Los Alamitos, CA, USA, 2012. IEEE CS Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. C. Bellettini, M. Camilli, L. Capra, and M. Monga. Distributed CTL Model Checking in the Cloud. ArXiv e-prints, Oct. 2013.Google ScholarGoogle Scholar
  8. C. Bellettini, M. Camilli, L. Capra, and M. Monga. Mardigras: Simplified building of reachability graphs on large clusters. In P. Abdulla and I. Potapov, editors, Reachability Problems, volume 8169 of LNCS, pages 83–95. Springer Berlin Heidelberg, 2013.Google ScholarGoogle Scholar
  9. M. C. Boukala and L. Petrucci. Distributed model-checking and counterexample search for CTL logic. Int. J. Crit. Comput.-Based Syst., 3(1/2):44–59, Jan. 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. M. Bourahla. Distributed ctl model checking. Software, IEE Proceedings -, 152(6):297–308, 2005.Google ScholarGoogle ScholarCross RefCross Ref
  11. M. Camilli. Petri nets state space analysis in the cloud. In Proceedings of the 2012 International Conference on Software Engineering, ICSE 2012, pages 1638–1640, Piscataway, NJ, USA, 2012. IEEE Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. G. Ciardo. Automated parallelization of discrete state-space generation. J. Parallel Distrib. Comput., 47(2):153–167, Dec. 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. G. Ciardo, J. Gluckman, and D. Nicol. Distributed state space generation of discrete-state stochastic models. INFORMS J. on Comp., 10(1):82–93, Jan. 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. E. M. Clarke, Jr., O. Grumberg, and D. A. Peled. Model checking. MIT Press, Cambridge, MA, USA, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. J. Dean and S. Ghemawat. MapReduce: simplified data processing on large clusters. Commun. ACM, 51:107–113, January 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. C. Eisner and D. Peled. Comparing symbolic and explicit model checking of a software system. In Proceedings of the 9th International SPIN Workshop on Model Checking of Software, pages 230–239, London, UK, UK, 2002. Springer-Verlag. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. J. Ekanayake, H. Li, B. Zhang, T. Gunarathne, S.-H. Bae, J. Qiu, and G. Fox. Twister: a runtime for iterative MapReduce. In Proc. of Symp. on High Performance Distributed Computing, pages 810–818, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. S. Evangelista, L. Petrucci, and S. Youcef. Parallel nested depth-first searches for ltl model checking. In T. Bultan and P.-A. Hsiung, editors, Automated Technology for Verification and Analysis, volume 6996 of LNCS, pages 381–396. Springer Berlin Heidelberg, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. R. Jhala and R. Majumdar. Software model checking. ACM Comput. Surv., 41(4):21:1–21:54, Oct. 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. F. Kordon et al. Web report on the model checking contest @ petri net 2013, available at http://mcc.lip6.fr, June 2013.Google ScholarGoogle Scholar
  21. F. Lerda and R. Sisto. Distributed-memory model checking with spin. In Proceedings of the 5th and 6th International SPIN Workshops on Theoretical and Practical Aspects of SPIN Model Checking, pages 22–39, London, UK, UK, 1999. Springer-Verlag. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. J. Lin and M. Schatz. Design patterns for efficient graph algorithms in mapreduce. In Mining and Learning with Graphs, pages 78–85, New York, 2010. ACM Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. U. Stern and D. Dill. Parallelizing the mur¨I¸ T verifier. Formal Methods in System Design, 18(2):117–129, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. C. t. Chu, S. K. Kim, Y. a. Lin, Y. Yu, G. R. Bradski, A. Y. Ng, and K. Olukotun. Map-Reduce for Machine Learning on Multicore. In Neural Information Processing Systems, pages 281–288, 2006.Google ScholarGoogle Scholar
  25. A. Tarski. A lattice-theoretical fixpoint theorem and its applications. Pacific Journal of Mathematics, 5:285–309, 1955.Google ScholarGoogle ScholarCross RefCross Ref
  26. The Apache Software Foundation. Hadoop MapReduce. http://hadoop.apache.org/mapreduce/, 2007. Last visited: June 2013.Google ScholarGoogle Scholar
  27. A. Valmari. The state explosion problem. In Lectures on Petri Nets I, pages 429–528, London, UK, 1998. Springer-Verlag.Google ScholarGoogle Scholar

Index Terms

  1. Formal verification problems in a big data world: towards a mighty synergy

                  Recommendations

                  Comments

                  Login options

                  Check if you have access through your login credentials or your institution to get full access on this article.

                  Sign in
                  • Published in

                    cover image ACM Conferences
                    ICSE Companion 2014: Companion Proceedings of the 36th International Conference on Software Engineering
                    May 2014
                    741 pages
                    ISBN:9781450327688
                    DOI:10.1145/2591062

                    Copyright © 2014 ACM

                    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

                    Publisher

                    Association for Computing Machinery

                    New York, NY, United States

                    Publication History

                    • Published: 31 May 2014

                    Permissions

                    Request permissions about this article.

                    Request Permissions

                    Check for updates

                    Qualifiers

                    • Article

                    Acceptance Rates

                    Overall Acceptance Rate276of1,856submissions,15%

                    Upcoming Conference

                    ICSE 2025

                  PDF Format

                  View or Download as a PDF file.

                  PDF

                  eReader

                  View online with eReader.

                  eReader