Abstract
Statistical model checking is a powerful and flexible approach for formal verification of computational models, e.g. P systems, which can have very large search spaces. Various statistical model checking tools have been developed, but choosing the most efficient and appropriate tool requires a significant degree of experience, not only because different tools have different modelling and property specification languages, but also because they may be designed to support only a certain subset of property types. Furthermore, their performance can vary depending on the property types and membrane systems being verified. In this paper, we evaluate the performance of various common statistical model checkers based on a pool of biological models. Our aim is to help users select the most suitable SMC tools from among the available options, by comparing their modelling and property specification languages, capabilities and performances.
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References
Alur, R., Henzinger, T.A.: Reactive modules. Form. Methods Syst. Des. 15(1), 7–48 (1999). http://dx.doi.org/10.1023/A:1008739929481
Aziz, A., Sanwal, K., Singhal, V., Brayton, R.: Model-checking continuous-time markov chains. ACM Trans. Comput. Logic 1(1), 162–170 (2000). http://doi.acm.org/10.1145/343369.343402
Baier, C., Haverkort, B., Hermanns, H., Katoen, J.P.: Model-checking algorithms for continuous-time markov chains. IEEE Trans. Softw. Eng. 29(6), 524–541 (2003)
Baier, C., Katoen, J.P.: Principles of Model Checking. The MIT Press, Cambridge (2008)
Bakir, M.E., Konur, S., Gheorghe, M., Niculescu, I., Ipate, F.: High performance simulations of kernel P systems. In: 2014 IEEE 16th International Conference on High Performance Computing and Communications (HPCC) (2014)
Bakir, M.E., Stannett, M.: Selection criteria for statistical model checking. In: Gheorghe, M., Konur, S. (eds.) Proceedings of the Workshop on Membrane Computing WMC 2016, Manchester (UK), 11–15 July 2016, pp. 55–57 (2016). http://bradscholars.brad.ac.uk/handle/10454/8840, Available as: Technical Report UB-20160819-1, University of Bradford
Bernardini, F., Gheorghe, M., Romero-Campero, F.J., Walkinshaw, N.: A hybrid approach to modeling biological systems. In: Eleftherakis, G., Kefalas, P., Păun, G., Rozenberg, G., Salomaa, A. (eds.) WMC 2007. LNCS, vol. 4860, pp. 138–159. Springer, Heidelberg (2007). doi:10.1007/978-3-540-77312-2_9
Blakes, J., Twycross, J., Romero-Campero, F.J., Krasnogor, N.: The infobiotics workbench: An integrated in silico modelling platform for systems and synthetic biology. Bioinformatics 27(23), 3323–3324 (2011)
Blakes, J., Twycross, J., Konur, S., Romero-Campero, F.J., Krasnogor, N., Gheorghe, M.: Infobiotics workbench: A P systems based tool for systems and synthetic biology. In: Frisco, P., Gheorghe, M., Pérez-Jiménez, M.J. (eds.) Applications of Membrane Computing in Systems and Synthetic Biology. Emergence, Complexity and Computation, vol. 7, pp. 1–41. Springer, Heidelberg (2014). doi:10.1007/978-3-319-03191-0_1
Bollig-Fischer, A., Marchetti, L., Mitrea, C., Wu, J., Kruger, A., Manca, V., Drăghici, S.: Modeling time-dependent transcription effects of HER2 oncogene and discovery of a role for E2F2 in breast cancer cell-matrix adhesion. Bioinformatics 30(21), 3036–3043 (2014)
Boyer, B., Corre, K., Legay, A., Sedwards, S.: PLASMA-lab: A flexible, distributable statistical model checking library. In: Joshi, K., Siegle, M., Stoelinga, M., D’Argenio, P.R. (eds.) QEST 2013. LNCS, vol. 8054, pp. 160–164. Springer, Heidelberg (2013). doi:10.1007/978-3-642-40196-1_12
Buchholz, P.: A new approach combining simulation and randomization for the analysis of large continuous time Markov chains. ACM Trans. Model Comput. Simul. 8(2), 194–222 (1998). http://doi.acm.org/10.1145/280265.280274
Carrillo, M., Góngora, P.A., Rosenblueth, D.A.: An overview of existing modeling tools making use of model checking in the analysis of biochemical networks. Front. Plant Sci. 3(155), 1–13 (2012)
Cavaliere, M., Mazza, T., Sedwards, S.: Statistical model checking of membrane systems with peripheral proteins: Quantifying the role of estrogen incellular mitosis and DNA damage. In: Frisco, P., Gheorghe, M., Pérez-Jiménez, M.J. (eds.) Applications of Membrane Computing inSystems and Synthetic Biology. Emergence, Complexity and Computation, vol. 7, pp. 43–63. Springer, Heidelberg (2014). doi:10.1007/978-3-319-03191-0_2
Clarke, E.M., Grumberg, O., Peled, D.: Model Checking. MIT Press, Cambridge (1999)
Donaldson, R., Gilbert, D.: A Monte Carlo model checker for Probabilistic LTL with numerical constraints. Technical report, University of Glasgow, Department of Computing Science (2008)
Dragomir, C., Ipate, F., Konur, S., Lefticaru, R., Mierla, L.: Model checking kernel P systems. In: Alhazov, A., Cojocaru, S., Gheorghe, M., Rogozhin, Y., Rozenberg, G., Salomaa, A. (eds.) CMC 2013. LNCS, vol. 8340, pp. 151–172. Springer, Heidelberg (2014). doi:10.1007/978-3-642-54239-8_12
Dwyer, M.B., Avrunin, G.S., Corbett, J.C.: Patterns in property specifications for finite-state verification. In: ICSE 1999, pp. 411–420. ACM, New York (1999)
The European Bioinformatics Institute. http://www.ebi.ac.uk/. Accessed 25 Sept 2016
Fisher, J., Piterman, N.: Model checking in biology. In: Kulkarni, V.V., Stan, G.-B., Raman, K. (eds.) A Systems Theoretic Approach to Systems and Synthetic Biology I Models and System Characterizations, pp. 255–279. Springer, Heidelberg (2014)
Fisher, J., Henzinger, T.A.: Executable cell biology. Nat. Biotech. 25(11), 1239–1249 (2007)
Frisco, P., Gheorghe, M., Pérez-Jiménez, M.J. (eds.): Applications of Membrane Computing in Systems and Synthetic Biology. Emergence, Complexity and Computation, vol. 7. Springer, Heidelberg (2014)
Gheorghe, M., Konur, S., Ipate, F., Mierla, L., Bakir, M.E., Stannett, M.: An integrated model checking toolset for kernel P systems. In: Rozenberg, G., Salomaa, A., Sempere, J.M., Zandron, C. (eds.) CMC 2015. LNCS, vol. 9504, pp. 153–170. Springer, Cham (2015). doi:10.1007/978-3-319-28475-0_11
Grunske, L.: Specification patterns for probabilistic quality properties. In: ICSE 2008, pp. 31–40. ACM, New York (2008)
Harel, D.: Statecharts: a visual formalism for complex systems. Sci. Comput. Program. 8(3), 231–274 (1987)
Heiner, M., Gilbert, D., Donaldson, R.: Petri nets for systems and synthetic biology. In: Bernardo, M., Degano, P., Zavattaro, G. (eds.) SFM 2008. LNCS, vol. 5016, pp. 215–264. Springer, Heidelberg (2008). doi:10.1007/978-3-540-68894-5_7
Hinton, A., Kwiatkowska, M., Norman, G., Parker, D.: PRISM: A tool for automatic verification of probabilistic systems. In: Hermanns, H., Palsberg, J. (eds.) TACAS 2006. LNCS, vol. 3920, pp. 441–444. Springer, Heidelberg (2006). doi:10.1007/11691372_29
Huth, M., Ryan, M.: Logic in Computer Science: Modelling and Reasoning about Systems, 2nd edn. Cambridge University Press, Cambridge (2004)
Katoen, J.P., Zapreev, I.S., Hahn, E.M., Hermanns, H., Jansen, D.N.: The ins and outs of the probabilistic model checker MRMC. In: Quantitative Evaluation of Systems (QEST), pp. 167–176. IEEE Computer Society (2009)
Kauffman, S.A.: Metabolic stability and epigenesis in randomly constructed genetic nets. J. Theoret. Biol. 22, 437–467 (1969)
Konur, S., Gheorghe, M.: A property-driven methodology for formal analysis of synthetic biology systems. IEEE/ACM Trans. Comput. Biol. Bioinform. 12(2), 360–371 (2015)
kPWorkbench. http://kpworkbench.org/. Accessed 25 Sept 2016
Kwiatkowska, M., Norman, G., Parker, D.: PRISM: Probabilistic symbolic model checker. In: Field, T., Harrison, P.G., Bradley, J., Harder, U. (eds.) TOOLS 2002. LNCS, vol. 2324, pp. 200–204. Springer, Heidelberg (2002). doi:10.1007/3-540-46029-2_13
Kwiatkowska, M., Norman, G., Parker, D.: Stochastic model checking. In: Bernardo, M., Hillston, J. (eds.) SFM 2007. LNCS, vol. 4486, pp. 220–270. Springer, Heidelberg (2007). doi:10.1007/978-3-540-72522-0_6
Legay, A., Delahaye, B., Bensalem, S.: Statistical model checking: An overview. In: Barringer, H., Falcone, Y., Finkbeiner, B., Havelund, K., Lee, I., Pace, G., Roşu, G., Sokolsky, O., Tillmann, N. (eds.) RV 2010. LNCS, vol. 6418, pp. 122–135. Springer, Heidelberg (2010). doi:10.1007/978-3-642-16612-9_11
Lindenmayer, A., Jürgensen, H.: Grammars of development: Discrete-state models for growth, differentiation, and gene expression in modular organisms. In: Rozenberg, G., Salomaa, A. (eds.) Lindenmayer Systems: Impacts on Theoretical Computer Science, Computer Graphics, and Developmental Biology, pp. 3–21. Springer, Heidelberg (1992). doi:10.1007/978-3-642-58117-5_1
Manca, V.: Infobiotics: Information in Biotic Systems. Emergence, Complexity and Computation, vol. 3. Springer, Heidelberg (2013)
Milner, R.: Communicating and Mobile Systems: The Pi-Calculus. Cambridge University Press, New York (1999)
Monteiro, P.T., Ropers, D., Mateescu, R., Freitas, A.T., de Jong, H.: Temporal logic patterns for querying dynamic models of cellular interaction networks. Bioinformatics 24(16), i227–i233 (2008). http://dx.doi.org/10.1093/bioinformatics/btn275
Markow Reward Model Checker (MRMC). http://www.mrmc-tool.org/. Accessed 18 Feb 2015
Pérez-Jiménez, M.J., Romero-Campero, F.J.: P systems, a new computational modelling tool for systems biology. In: Priami, C., Plotkin, G. (eds.) Transactions on Computational Systems Biology VI. LNCS, vol. 4220, pp. 176–197. Springer, Heidelberg (2006). doi:10.1007/11880646_8
Plasma-Lab. https://project.inria.fr/plasma-lab/. Accessed 18 Feb 2015
Reisig, W.: The basic concepts. In: Understanding Petri Nets: Modeling Techniques, Analysis Methods, Case Studies, pp. 13–24. Springer, Heidelberg (2013). http://dx.doi.org/10.1007/978-3-642-33278-4_2
Probabilistic and Symbolic Model Checker (PRISM). http://www.prismmodelchecker.org/. Accessed 08 Jan 2015
Sanassy, D., Widera, P., Krasnogor, N.: Meta-stochastic simulation of biochemical models for systems and synthetic biology. ACS Synth. Biol. 4(1), 39–47 (2015). pMID: 25152014. http://dx.doi.org/10.1021/sb5001406
Ymer website. http://www.tempastic.org/ymer/. Accessed 25 Aug 2015
Younes, H., Kwiatkowska, M., Norman, G., Parker, D.: Numerical vs. statistical probabilistic model checking. Int. J. Softw. Tools Technol. Transfer (STTT) 8(3), 216–228 (2006)
Younes, H.L.S.: Ymer: A statistical model checker. In: Etessami, K., Rajamani, S.K. (eds.) CAV 2005. LNCS, vol. 3576, pp. 429–433. Springer, Heidelberg (2005). doi:10.1007/11513988_43
Younes, H.L.S., Simmons, R.G.: Probabilistic verification of discrete event systems using acceptance sampling. In: Brinksma, E., Larsen, K.G. (eds.) CAV 2002. LNCS, vol. 2404, pp. 223–235. Springer, Heidelberg (2002). doi:10.1007/3-540-45657-0_17
Zapreev, I.S., Jansen, C.: Markov reward model checker manual. http://www.mrmc-tool.org/downloads/MRMC/Specs/MRMC_Manual.pdf
Zuliani, P.: Statistical model checking for biological applications. Int. J. Softw. Tools Technol. Transfer 17(4), 527–536 (2014). http://dx.doi.org/10.1007/s10009-014-0343-0
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Bakir, M.E., Gheorghe, M., Konur, S., Stannett, M. (2017). Comparative Analysis of Statistical Model Checking Tools. In: Leporati, A., Rozenberg, G., Salomaa, A., Zandron, C. (eds) Membrane Computing. CMC 2016. Lecture Notes in Computer Science(), vol 10105. Springer, Cham. https://doi.org/10.1007/978-3-319-54072-6_8
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