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Components in Probabilistic Systems: Suitable by Construction

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Leveraging Applications of Formal Methods, Verification and Validation: Verification Principles (ISoLA 2020)

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Abstract

This paper focusses on the question when and to what extent a particular system component can be considered suitable to use in the context of the dynamics of a larger technical system. We introduce different notions of suitability that arise naturally in the context of probabilistic nondeterministic systems that interact through the exchange of messages in the style of input-output automata. Besides discussing algorithmic aspects for an analysis following our notions of suitability, we demonstrate practical usability of our concepts by means of experiments on a concrete use case.

Authors are listed in alphabetical order. This work was partially supported by the DFG under the projects TRR 248 (see https://perspicuous-computing.science, project ID 389792660), EXC 2050/1 (CeTI, project ID 390696704, as part of Germany’s Excellence Strategy), BA-1679/11-1, and BA-1679/12-1, the ERC Advanced Investigators Grant 695614 (POWVER), and the Key-Area Research and Development Program Grant 2018B010107004 of Guangdong Province.

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Notes

  1. 1.

    https://doi.org/10.5281/zenodo.3970766 [6].

  2. 2.

    Also exploiting variable-reordering techniques from [27] on the generated model.

References

  1. Test-ablauf - So testet die Stiftung Warentest. https://www.test.de/unternehmen/testablauf-5017344-0/. Accessed 30 June 2020

  2. The Official Site of The European New Car Assessment Programme. https://www.euroncap.com/en/. Accessed 30 June 2020

  3. Alur, R.: Principles of Cyber-Physical Systems. The MIT Press, Cambridge (2015)

    Google Scholar 

  4. Apel, S., Batory, D., Kästner, C., Saake, G.: Feature-Oriented Software Product Lines: Concepts and Implementation. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-37521-7

    Book  Google Scholar 

  5. Apel, S., Kästner, C.: An overview of feature-oriented software development. J. Object Technol. 8, 49–84 (2009)

    Article  Google Scholar 

  6. Baier, C., Dubslaff, C., Hermanns, H., Klauck, M., Klüppelholz, S., Köhl, M.A.: Tooling, Data and Results for “Components in Probabilistic Systems: Suitable by Construction” (2020). https://doi.org/10.5281/zenodo.3970766

  7. Baier, C., Dubslaff, C., Klüppelholz, S.: Trade-off analysis meets probabilistic model checking. In: Proceedings of the 23rd Conference on Computer Science Logic and the 29th Symposium on Logic in Computer Science (CSL-LICS), pp. 1:1–1:10. ACM (2014)

    Google Scholar 

  8. Baier, C., Größer, M., Bertrand, N.: Probabilistic \(\omega \)-automata. J. ACM 59(1), 1:1–1:52 (2012)

    Article  MathSciNet  Google Scholar 

  9. Barto, A.G., Bradtke, S.J., Singh, S.P.: Learning to act using real-time dynamic programming. Artif. Intell. 72(1–2), 81–138 (1995)

    Article  Google Scholar 

  10. Bonet, B., Geffner, H.: Labeled RTDP: improving the convergence of real-time dynamic programming. In: ICAPS, pp. 12–21 (2003)

    Google Scholar 

  11. Canetti, R., et al.: Task-structured probabilistic I/O automata. J. Comput. Syst. Sci. 94, 63–97 (2018). https://doi.org/10.1016/j.jcss.2017.09.007

    Article  MathSciNet  MATH  Google Scholar 

  12. Chatterjee, K., Majumdar, R., Henzinger, T.: Markov decision processes with multiple objectives. In: STACS, February 2006. http://chess.eecs.berkeley.edu/pubs/81.html

  13. Chen, T., Forejt, V., Kwiatkowska, M., Simaitis, A., Wiltsche, C.: On stochastic games with multiple objectives. In: Chatterjee, K., Sgall, J. (eds.) MFCS 2013. LNCS, vol. 8087, pp. 266–277. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40313-2_25

    Chapter  Google Scholar 

  14. Cheung, L., Lynch, N.A., Segala, R., Vaandrager, F.W.: Switched PIOA: parallel composition via distributed scheduling. Theor. Comput. Sci. 365(1–2), 83–108 (2006). https://doi.org/10.1016/j.tcs.2006.07.033

    Article  MathSciNet  MATH  Google Scholar 

  15. Chrszon, P., Dubslaff, C., Klüppelholz, S., Baier, C.: ProFeat: feature-oriented engineering for family-based probabilistic model checking. Formal Aspects Comput. 30(1), 45–75 (2018). https://doi.org/10.1007/s00165-017-0432-4

    Article  MathSciNet  Google Scholar 

  16. Classen, A., Heymans, P., Schobbens, P.Y., Legay, A., Raskin, J.F.: Model checking lots of systems: efficient verification of temporal properties in software product lines. In: Proceedings of ICSE 2010, pp. 335–344. ACM (2010)

    Google Scholar 

  17. Czarnecki, K., Eisenecker, U.W.: Generative Programming: Methods, Tools, and Applications. ACM Press/Addison-Wesley Publishing Co., New York (2000)

    Google Scholar 

  18. Dubslaff, C., Baier, C., Klüppelholz, S.: Probabilistic model checking for feature-oriented systems. Trans. Aspect-Oriented Softw. Dev. 12, 180–220 (2015). https://doi.org/10.1007/978-3-662-46734-3_5

    Article  Google Scholar 

  19. Etessami, K., Kwiatkowska, M., Vardi, M., Yannakakis, M.: Multi-objective model checking of Markov decision processes. Log. Methods Comput. Sci. 4(4), 1–21 (2008)

    MathSciNet  MATH  Google Scholar 

  20. Forejt, V., Kwiatkowska, M., Parker, D.: Pareto curves for probabilistic model checking. In: Chakraborty, S., Mukund, M. (eds.) ATVA 2012. LNCS, pp. 317–332. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33386-6_25

    Chapter  MATH  Google Scholar 

  21. Forejt, V., Kwiatkowska, M.Z., Norman, G., Parker, D., Qu, H.: Quantitative multi-objective verification for probabilistic systems. In: Abdulla, P.A., Leino, K.R.M. (eds.) TACAS 2011. LNCS, vol. 6605, pp. 112–127. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-19835-9_11

    Chapter  MATH  Google Scholar 

  22. Gardner, M.: Mathematical games. Sci. Am. 229, 118–121 (1973)

    Article  Google Scholar 

  23. Giro, S., D’Argenio, P.R., Fioriti, L.M.F.: Distributed probabilistic input/output automata: expressiveness, (un)decidability and algorithms. Theor. Comput. Sci. 538, 84–102 (2014). https://doi.org/10.1016/j.tcs.2013.07.017. Quantitative Aspects of Programming Languages and Systems (2011–12)

    Article  MathSciNet  MATH  Google Scholar 

  24. van Glabbeek, R.J., Smolka, S.A., Steffen, B.: Reactive, generative and stratified models of probabilistic processes. Inf. Comput. 121(1), 59–80 (1995). https://doi.org/10.1006/inco.1995.1123

    Article  MathSciNet  MATH  Google Scholar 

  25. Gros, T.P., Hermanns, H., Hoffmann, J., Klauck, M., Steinmetz, M.: Deep statistical model checking. In: Gotsman, A., Sokolova, A. (eds.) FORTE 2020. LNCS, vol. 12136, pp. 96–114. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-50086-3_6

    Chapter  Google Scholar 

  26. Hoare, C.A.R.: Communicating sequential processes. Commun. ACM 21(8), 666–677 (1978). https://doi.org/10.1145/359576.359585

    Article  MATH  Google Scholar 

  27. Klein, J., et al.: Advances in probabilistic model checking with PRISM: variable reordering, quantiles and weak deterministic Büchi automata. Int. J. Softw. Tools Technol. Transf. 20(2), 179–194 (2017). https://doi.org/10.1007/s10009-017-0456-3

    Article  Google Scholar 

  28. Köhl, M.A., Hermanns, H., Biewer, S.: Efficient monitoring of real driving emissions. In: Colombo, C., Leucker, M. (eds.) RV 2018. LNCS, vol. 11237, pp. 299–315. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-03769-7_17

    Chapter  MATH  Google Scholar 

  29. Kwiatkowska, M., Norman, G., Parker, D.: PRISM 4.0: verification of probabilistic real-time systems. In: Gopalakrishnan, G., Qadeer, S. (eds.) CAV 2011. LNCS, vol. 6806, pp. 585–591. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-22110-1_47

    Chapter  Google Scholar 

  30. Lee, E.A.: Cyber physical systems: design challenges. In: 2008 11th IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing (ISORC), pp. 363–369 (2008)

    Google Scholar 

  31. Lovejoy, W.S.: A survey of algorithmic methods for partially observable Markov decision processes. Ann. Oper. Res. 28(1), 47–65 (1991)

    Article  MathSciNet  Google Scholar 

  32. Lynch, N., Tuttle, M.: An introduction to input/output automata. CWI Q. 2(3), 219–246 (1989)

    MathSciNet  MATH  Google Scholar 

  33. Madani, O., Hanks, S., Condon, A.: On the undecidability of probabilistic planning and related stochastic optimization problems. Artif. Intell. 147(1–2), 5–34 (2003)

    Article  MathSciNet  Google Scholar 

  34. Milner, R.: Communication and Concurrency. PHI Series in Computer Science. Prentice Hall, Upper Saddle River (1989)

    MATH  Google Scholar 

  35. Papadimitriou, C., Tsitsiklis, J.: The complexity of Markov decision processes. Math. Oper. Res. 12(3), 441–450 (1987)

    Article  MathSciNet  Google Scholar 

  36. Pineda, L.E., Zilberstein, S.: Planning under uncertainty using reduced models: revisiting determinization. In: ICAPS (2014)

    Google Scholar 

  37. Puterman, M.: Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley, New York (1994)

    Book  Google Scholar 

  38. Segala, R.: Modeling and verification of randomized distributed real-time systems. Ph.D. thesis, Massachusetts Institute of Technology (1995)

    Google Scholar 

  39. Thüm, T., Apel, S., Kästner, C., Schaefer, I., Saake, G.: A classification and survey of analysis strategies for software product lines. ACM Comput. Surv. 47(1s), 6:1–6:45 (2014)

    Google Scholar 

  40. Wu, S., Smolka, S.A., Stark, E.W.: Composition and behaviors of probabilistic I/O automata. Theor. Comput. Sci. 176(1–2), 1–38 (1997). https://doi.org/10.1016/S0304-3975(97)00056-X

    Article  MathSciNet  MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Technische Universität Dresden, Dresden, Germany

    Christel Baier, Clemens Dubslaff & Sascha Klüppelholz

  2. Saarland University, Saarland Informatics Campus, Saarbrücken, Germany

    Holger Hermanns, Michaela Klauck & Maximilian A. Köhl

  3. Institute of Intelligent Software, Guangzhou, China

    Holger Hermanns

Authors
  1. Christel Baier
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  2. Clemens Dubslaff
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  3. Holger Hermanns
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  4. Michaela Klauck
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  5. Sascha Klüppelholz
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  6. Maximilian A. Köhl
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Corresponding authors

Correspondence to Christel Baier , Clemens Dubslaff , Holger Hermanns , Michaela Klauck , Sascha Klüppelholz or Maximilian A. Köhl .

Editor information

Editors and Affiliations

  1. Lero, Limerick, Ireland

    Tiziana Margaria

  2. TU Dortmund, Dortmund, Germany

    Bernhard Steffen

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Baier, C., Dubslaff, C., Hermanns, H., Klauck, M., Klüppelholz, S., Köhl, M.A. (2020). Components in Probabilistic Systems: Suitable by Construction. In: Margaria, T., Steffen, B. (eds) Leveraging Applications of Formal Methods, Verification and Validation: Verification Principles. ISoLA 2020. Lecture Notes in Computer Science(), vol 12476. Springer, Cham. https://doi.org/10.1007/978-3-030-61362-4_13

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  • DOI: https://doi.org/10.1007/978-3-030-61362-4_13

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