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On-Line Monitoring for Temporal Logic Robustness

  • Adel Dokhanchi
  • Bardh Hoxha
  • Georgios Fainekos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8734)

Abstract

In this paper, we provide a Dynamic Programming algorithm for on-line monitoring of the state robustness of Metric Temporal Logic specifications with past time operators. We compute the robustness of MTL with unbounded past and bounded future temporal operators (MTL\(^{<+\infty}_{+pt}\)) over sampled traces of Cyber-Physical Systems. We implemented our tool in Matlab as a Simulink block that can be used in any Simulink model. We experimentally demonstrate that the overhead of the MTL\(^{<+\infty}_{+pt}\) robustness monitoring is acceptable for certain classes of practical specifications.

Keywords

Temporal Logic Unman Aerial Vehicle Linear Temporal Logic Execution Trace Runtime Overhead 
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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References

  1. 1.
    Alur, R., Courcoubetis, C., Halbwachs, N., Henzinger, T.A., Ho, P.H., Nicollin, X., Olivero, A., Sifakis, J., Yovine, S.: The algorithmic analysis of hybrid systems. Theoretical Computer Science 138, 3–34 (1995)MathSciNetCrossRefzbMATHGoogle Scholar
  2. 2.
    Finkbeiner, B., Kuhtz, L.: Monitor circuits for ltl with bounded and unbounded future. In: Bensalem, S., Peled, D.A. (eds.) RV 2009. LNCS, vol. 5779, pp. 60–75. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  3. 3.
    Havelund, K., Rosu, G.: Monitoring programs using rewriting. In: Proceedings of the 16th IEEE International Conference on Automated Software Engineering (2001)Google Scholar
  4. 4.
    Havelund, K., Roşu, G.: Synthesizing monitors for safety properties. In: Katoen, J.-P., Stevens, P. (eds.) TACAS 2002. LNCS, vol. 2280, pp. 342–356. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  5. 5.
    Havelund, K., Rosu, G.: Efficient monitoring of safety properties. STTT 6, 158–173 (2004)CrossRefGoogle Scholar
  6. 6.
    Kristoffersen, K.J., Pedersen, C., Andersen, H.R.: Runtime verification of timed LTL using disjunctive normalized equation systems. In: Proceedings of the 3rd Workshop on Run-time Verification. ENTCS, vol. 89, pp. 1–16 (2003)Google Scholar
  7. 7.
    Maler, O., Nickovic, D.: Monitoring temporal properties of continuous signals. In: Lakhnech, Y., Yovine, S. (eds.) FORMATS/2004. LNCS, vol. 3253, pp. 152–166. Springer, Heidelberg (2004)Google Scholar
  8. 8.
    Reinbacher, T., Rozier, K.Y., Schumann, J.: Temporal-logic based runtime observer pairs for system health management of real-time systems. In: Ábrahám, E., Havelund, K. (eds.) TACAS 2014. LNCS, vol. 8413, pp. 357–372. Springer, Heidelberg (2014)Google Scholar
  9. 9.
    Rosu, G., Havelund, K.: Synthesizing dynamic programming algorithms from linear temporal logic formulae. Technical report, Research Institute for Advanced Computer Science (RIACS) (2001)Google Scholar
  10. 10.
    Tan, L., Kim, J., Sokolsky, O., Lee, I.: Model-based testing and monitoring for hybrid embedded systems. In: Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, pp. 487–492 (2004)Google Scholar
  11. 11.
    Thati, P., Rosu, G.: Monitoring algorithms for metric temporal logic specifications. In: Runtime Verification. ENTCS, vol. 113, pp. 145–162. Elsevier (2005)Google Scholar
  12. 12.
    Basin, D., Klaedtke, F., Zălinescu, E.: Algorithms for monitoring real-time properties. In: Khurshid, S., Sen, K. (eds.) RV 2011. LNCS, vol. 7186, pp. 260–275. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  13. 13.
    Geilen, M.: On the construction of monitors for temporal logic properties. In: Proceedings of the 1st Workshop on Runtime Verification. ENTCS, vol. 55, pp. 181–199 (2001)Google Scholar
  14. 14.
    Maler, O., Nickovic, D., Pnueli, A.: From MITL to Timed Automata. In: Asarin, E., Bouyer, P. (eds.) FORMATS 2006. LNCS, vol. 4202, pp. 274–289. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  15. 15.
    Pnueli, A.: The temporal logic of programs. In: Proceedings of the 18th IEEE Symposium Foundations of Computer Science, pp. 46–57 (1977)Google Scholar
  16. 16.
    Koymans, R.: Specifying real-time properties with metric temporal logic. Real-Time Systems 2, 255–299 (1990)CrossRefGoogle Scholar
  17. 17.
    Fainekos, G., Pappas, G.J.: Robustness of temporal logic specifications. In: Havelund, K., Núñez, M., Roşu, G., Wolff, B. (eds.) FATES/RV 2006. LNCS, vol. 4262, pp. 178–192. Springer, Heidelberg (2006)Google Scholar
  18. 18.
    Fainekos, G., Pappas, G.J.: Robustness of temporal logic specifications for continuous-time signals. Theor. Comput. Sci. 410, 4262–4291 (2009)MathSciNetCrossRefzbMATHGoogle Scholar
  19. 19.
    Donzé, A., Ferrère, T., Maler, O.: Efficient robust monitoring for stl. In: Sharygina, N., Veith, H. (eds.) CAV 2013. LNCS, vol. 8044, pp. 264–279. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  20. 20.
    Garcia, C.E., Prett, D.M., Morari, M.: Model predictive control: Theory and practice - a survey. Automatica 25, 335–348 (1989)CrossRefzbMATHGoogle Scholar
  21. 21.
    Abbas, H., Fainekos, G.E., Sankaranarayanan, S., Ivancic, F., Gupta, A.: Probabilistic temporal logic falsification of cyber-physical systems. ACM Trans. Embedded Comput. Syst. 12, 95 (2013)CrossRefGoogle Scholar
  22. 22.
    Jin, X., Donze, A., Deshmukh, J., Seshia, S.: Mining requirements from closed-loop control models. In: Hybrid Systems: Computation and Control. ACM Press (2013)Google Scholar
  23. 23.
    Seda, A.K., Hitzler, P.: Generalized distance functions in the theory of computation. The Computer Journal 53, 443–464 (2008)CrossRefGoogle Scholar
  24. 24.
    Eklund, J.M., Sprinkle, J., Sastry, S.: Implementing and testing a nonlinear model predictive tracking controller for aerial pursuit/evasion games on a fixed wing aircraft. In: American Control Conference (2005)Google Scholar
  25. 25.
    Bakirtzis, A., Petridis, V., Kiartzis, S., Alexiadis, M., Maissis, A.: A neural network short term load forecasting model for the greek power system. IEEE Transactions on Power Systems 11, 858–863 (1996)CrossRefGoogle Scholar
  26. 26.
    Monteiro, C., Bessa, R., Miranda, V., Botterud, A., Wang, J., Conzelmann, G.: Wind power forecasting: State-of-the-art 2009. Technical Report ANL/DIS-10-1, Argonne National Laboratory (2009)Google Scholar
  27. 27.
    Davey, B.A., Priestley, H.A.: Introduction to Lattices and Order, 2nd edn. Cambridge University Press (2002)Google Scholar
  28. 28.
    Fainekos, G., Sankaranarayanan, S., Ueda, K., Yazarel, H.: Verification of automotive control applications using s-taliro. In: Proceedings of the American Control Conference (2012)Google Scholar
  29. 29.
    Simuquest: Enginuity (2013), http://www.simuquest.com/products/enginuity (accessed: October 14, 2013)
  30. 30.
    Annpureddy, Y., Liu, C., Fainekos, G., Sankaranarayanan, S.: S-taliro: A tool for temporal logic falsification for hybrid systems. In: Abdulla, P.A., Leino, K.R.M. (eds.) TACAS 2011. LNCS, vol. 6605, pp. 254–257. Springer, Heidelberg (2011)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Adel Dokhanchi
    • 1
  • Bardh Hoxha
    • 1
  • Georgios Fainekos
    • 1
  1. 1.School of Computing, Informatics and Decision Systems EngineeringArizona State UniversityUSA

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