Improving and Assessing the Efficiency of the MC4CSLTA Model Checker

  • Elvio Gilberto Amparore
  • Susanna Donatelli
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8168)

Abstract

CSLTA is a stochastic logic which is able to express properties on the behavior of a CTMC, in particular in terms of the possible executions of the CTMC (like the probability that the set of paths that exhibits a certain behavior is above/below a certain threshold). This paper presents the new version of the the stochastic model checker MC4CSLTA, which verifies CSLTA formulas against a Continuous Time Markov Chain, possibly expressed as a Generalized Stochastic Petri Net. With respect to the first version of the model checker presented in [1], version 2 features a totally new solution algorithm, which is able to verify complex, nested formulas based on the timed automaton, while, at the same time, is capable of reaching a time and space complexity similar to that of the CSL model checkers when the automaton specifies a neXt or an Until formulas. In particular, the goal of this paper is to present a new way of generating the MRP, which, together with the new MRP solution method presented in [2] provides the two cornerstone results which are at the basis of the current version. The model checker has been evaluated and validated against PRISM [3] (for whose CSLTA formulas which can be expressed in CSL) and against the statistical model checker Cosmos[4] (for all types of formulas).

Keywords

Model Checker Atomic Proposition Model Check Algorithm Clock Constraint Single Clock 
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.
This is a preview of subscription content, log in to check access.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Amparore, E.G., Donatelli, S.: MC4CSLTA: an efficient model checking tool for CSLTA. In: International Conference on Quantitative Evaluation of Systems, pp. 153–154. IEEE Computer Society, Los Alamitos (2010)Google Scholar
  2. 2.
    Amparore, E.G., Donatelli, S.: A component-based solution for reducible markov regenerative processes. Performance Evaluation 70, 400–422 (2013)CrossRefGoogle Scholar
  3. 3.
    Kwiatkowska, M., Norman, G., Parker, D.: PRISM: Probabilistic Model Checking for Performance and Reliability Analysis. Performance Evaluation 36, 40–45 (2009)CrossRefGoogle Scholar
  4. 4.
    Ballarini, P., Djafri, H., Duflot, M., Haddad, S., Pekergin, N.: COSMOS: a statistical model checker for the hybrid automata stochastic logic. In: Proceedings of the 8th International Conference on Quantitative Evaluation of Systems (QEST 2011), pp. 143–144. IEEE Computer Society Press, Aachen (2011)CrossRefGoogle Scholar
  5. 5.
    Aziz, A., Sanwal, K., Singhal, V., Brayton, R.: Model-checking continuous-time Markov chains. ACM Transactions on Computational Logic 1, 162–170 (2000)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Katoen, J.P., Zapreev, I.S., Hahn, E.M., Hermanns, H., Jansen, D.N.: The ins and outs of the probabilistic model checker MRMC. Performance Evaluation 68, 90–104 (2011)CrossRefGoogle Scholar
  7. 7.
    Heiner, M., Rohr, C., Schwarick, M.: Marcie - model checking and reachability analysis done efficiently. In: Colom, J.-M., Desel, J. (eds.) PETRI NETS 2013. LNCS, vol. 7927, pp. 389–399. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  8. 8.
    Donatelli, S., Haddad, S., Sproston, J.: Model checking timed and stochastic properties with CSLTA. IEEE Transactions on Software Engineering 35, 224–240 (2009)CrossRefGoogle Scholar
  9. 9.
    Alur, R., Dill, D.L.: A theory of timed automata. Theoretical Comp. Science 126, 183–235 (1994)MathSciNetMATHCrossRefGoogle Scholar
  10. 10.
    Chen, T., Han, T., Katoen, J.P., Mereacre, A.: Model checking of continuous-time Markov chains against timed automata specifications. Logical Methods in Computer Science 7 (2011)Google Scholar
  11. 11.
    Barbot, B., Chen, T., Han, T., Katoen, J.-P., Mereacre, A.: Efficient ctmc model checking of linear real-time objectives. In: Abdulla, P.A., Leino, K.R.M. (eds.) TACAS 2011. LNCS, vol. 6605, pp. 128–142. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  12. 12.
    Ballarini, P., Djafri, H., Duflot, M., Haddad, S., Pekergin, N.: HASL: An expressive language for statistical verification of stochastic models. In: Proceedings of the 5th International Conference on Performance Evaluation Methodologies and Tools (VALUETOOLS 2011), Cachan, France, pp. 306–315 (2011)Google Scholar
  13. 13.
    Amparore, E.G.: States, actions and path properties in Markov chains. PhD thesis, University of Torino, Italy (2013)Google Scholar
  14. 14.
    German, R.: Iterative analysis of Markov regenerative models. Performance Evaluation 44, 51–72 (2001)MATHCrossRefGoogle Scholar
  15. 15.
    Amparore, E.G., Donatelli, S.: Revisiting the Iterative Solution of Markov Regenerative Processes. Numerical Linear Algebra with Applications, Special Issue on Numerical Solutions of Markov Chains 18, 1067–1083 (2011)MathSciNetMATHCrossRefGoogle Scholar
  16. 16.
    Amparore, E.G., Donatelli, S.: Model Checking CSLTA with Deterministic and Stochastic Petri Nets. In: Proceedings of the 2010 IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). IEEE Computer Society Press (2010); DSN-PDS 2010Google Scholar
  17. 17.
    Amparore, E.G., Donatelli, S.: The MC4CSLTA model checker (2013), http://www.di.unito.it/~amparore/mc4cslta/
  18. 18.
    Baarir, S., Beccuti, M., Cerotti, D., Pierro, M.D., Donatelli, S., Franceschinis, G.: The GreatSPN tool: recent enhancements. SIGMETRICS Performance Evaluation Review 36, 4–9 (2009)CrossRefGoogle Scholar
  19. 19.
    Lecca, Priami: Cell Cycle Control in Eukaryotes - Prism case studies (2011), http://www.prismmodelchecker.org/casestudies/cyclin.php
  20. 20.
    Lecca, P., Priami, C.: Cell cycle control in eukaryotes: A BioSpi model. In: Proc. Workshop on Concurrent Models in Molecular Biology (BioConcur 2003). Electronic Notes in Theoretical Computer Science (2003)Google Scholar
  21. 21.
    van der Aalst, W.M.P.: Business process management demystified: A tutorial on models, systems and standards for workflow management. In: Desel, J., Reisig, W., Rozenberg, G. (eds.) ACPN 2003. LNCS, vol. 3098, pp. 1–65. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  22. 22.
    Amparore, E.G., Ballarini, P., Beccuti, M., Donatelli, S., Franceschinis, G.: Expressing and Computing Passage Time Measures of GSPN models with HASL. In: Colom, J.-M., Desel, J. (eds.) PETRI NETS 2013. LNCS, vol. 7927, pp. 110–129. Springer, Heidelberg (2013)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Elvio Gilberto Amparore
    • 1
  • Susanna Donatelli
    • 1
  1. 1.University of TorinoTorinoItaly

Personalised recommendations