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Monitorability Under Assumptions

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Runtime Verification (RV 2020)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12399))

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Abstract

We introduce the monitoring of trace properties under assumptions. An assumption limits the space of possible traces that the monitor may encounter. An assumption may result from knowledge about the system that is being monitored, about the environment, or about another, connected monitor. We define monitorability under assumptions and study its theoretical properties. In particular, we show that for every assumption A, the boolean combinations of properties that are safe or co-safe relative to A are monitorable under A. We give several examples and constructions on how an assumption can make a non-monitorable property monitorable, and how an assumption can make a monitorable property monitorable with fewer resources, such as integer registers.

This research was supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award).

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Notes

  1. 1.

    We follow the notation of [13] for temporal logic, where \(\mathcal {U}\) is the (strong) until operator, and \(\mathcal {W}\) is the unless (or weak until) operator.

References

  1. Alpern, B., Schneider, F.B.: Defining liveness. Inf. Process. Lett. 21(4), 181–185 (1985). https://doi.org/10.1016/0020-0190(85)90056-0. http://www.sciencedirect.com/science/article/pii/0020019085900560

    Article  MathSciNet  MATH  Google Scholar 

  2. Alpern, B., Schneider, F.B.: Recognizing safety and liveness. Distrib. Comput. 2(3), 117–126 (1987). https://doi.org/10.1007/BF01782772

    Article  MATH  Google Scholar 

  3. Bartocci, E., Falcone, Y., Francalanza, A., Reger, G.: Introduction to runtime verification. In: Bartocci, E., Falcone, Y. (eds.) Lectures on Runtime Verification. LNCS, vol. 10457, pp. 1–33. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-75632-5_1

    Chapter  Google Scholar 

  4. Bauer, A., Falcone, Y.: Decentralised LTL monitoring. In: Giannakopoulou, D., Méry, D. (eds.) FM 2012. LNCS, vol. 7436, pp. 85–100. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-32759-9_10

    Chapter  Google Scholar 

  5. Bauer, A., Leucker, M., Schallhart, C.: Runtime verification for LTL and TLTL. ACM Trans. Softw. Eng. Methodol. 20(4) (2011). https://doi.org/10.1145/2000799.2000800

  6. Chang, E., Manna, Z., Pnueli, A.: The safety-progress classification. In: Bauer, F.L., Brauer, W., Schwichtenberg, H. (eds.) Logic and Algebra of Specification. NATO ASI Series, vol. 94, pp. 143–202. Springer, Heidelberg (1993). https://doi.org/10.1007/978-3-642-58041-3_5

    Chapter  Google Scholar 

  7. Chen, F., Serbanuta, T., Rosu, G.: Jpredictor. In: 2008 ACM/IEEE 30th International Conference on Software Engineering, pp. 221–230 (2008). https://doi.org/10.1145/1368088.1368119

  8. Cimatti, A., Tian, C., Tonetta, S.: Assumption-based runtime verification with partial observability and resets. In: Finkbeiner, B., Mariani, L. (eds.) RV 2019. LNCS, vol. 11757, pp. 165–184. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-32079-9_10

    Chapter  Google Scholar 

  9. Diekert, V., Leucker, M.: Topology, monitorable properties and runtime verification. Theoret. Comput. Sci. 537, 29–41 (2014). https://doi.org/10.1016/j.tcs.2014.02.052

    Article  MathSciNet  MATH  Google Scholar 

  10. Falcone, Y., Fernandez, J.C., Mounier, L.: What can you verify and enforce at runtime? Sotfw. Tools Technol. Transf. (2011). https://hal.archives-ouvertes.fr/hal-00497350

  11. Ferrère, T., Henzinger, T.A., Saraç, N.E.: A theory of register monitors. In: Proceedings of the 33rd Annual ACM/IEEE Symposium on Logic in Computer Science, pp. 394–403 (2018). https://doi.org/10.1145/3209108.3209194

  12. Henzinger, T.A.: Sooner is safer than later. Inf. Process. Lett. 43(3), 135–141 (1992). https://doi.org/10.1016/0020-0190(92)90005-G. http://www.sciencedirect.com/science/article/pii/002001909290005G

    Article  MathSciNet  MATH  Google Scholar 

  13. Manna, Z., Pnueli, A.: The Temporal Logic of Reactive and Concurrent Systems - Specification. Springer, Heidelberg (1992). https://doi.org/10.1007/978-1-4612-0931-7

    Book  MATH  Google Scholar 

  14. Peled, D., Havelund, K.: Refining the safety–liveness classification of temporal properties according to monitorability. In: Margaria, T., Graf, S., Larsen, K.G. (eds.) Models, Mindsets, Meta: The What, the How, and the Why Not?. LNCS, vol. 11200, pp. 218–234. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-22348-9_14

    Chapter  Google Scholar 

  15. Petric Maretić, G., Torabi Dashti, M., Basin, D.: LTL is closed under topological closure. Inf. Process. Lett. 114(8), 408–413 (2014). https://doi.org/10.1016/j.ipl.2014.03.001. http://www.sciencedirect.com/science/article/pii/S0020019014000386

    Article  MathSciNet  MATH  Google Scholar 

  16. Pinisetty, S., Jéron, T., Tripakis, S., Falcone, Y., Marchand, H., Preoteasa, V.: Predictive runtime verification of timed properties. J. Syst. Softw. 132, 353–365 (2017). https://doi.org/10.1016/j.jss.2017.06.060. http://www.sciencedirect.com/science/article/pii/S0164121217301310

    Article  MATH  Google Scholar 

  17. Pnueli, A., Zaks, A.: PSL model checking and run-time verification via testers. In: Misra, J., Nipkow, T., Sekerinski, E. (eds.) FM 2006. LNCS, vol. 4085, pp. 573–586. Springer, Heidelberg (2006). https://doi.org/10.1007/11813040_38

    Chapter  Google Scholar 

  18. Zhang, X., Leucker, M., Dong, W.: Runtime verification with predictive semantics. In: Goodloe, A.E., Person, S. (eds.) NFM 2012. LNCS, vol. 7226, pp. 418–432. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-28891-3_37

    Chapter  Google Scholar 

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Authors and Affiliations

  1. IST Austria, Klosterneuburg, Austria

    Thomas A. Henzinger & N. Ege Saraç

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  1. Thomas A. Henzinger
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  2. N. Ege Saraç
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Correspondence to N. Ege Saraç .

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Editors and Affiliations

  1. University of Southern California, Los Angeles, CA, USA

    Jyotirmoy Deshmukh

  2. AIT Austrian Institute of Technology GmbH, Vienna, Austria

    Dejan Ničković

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Henzinger, T.A., Saraç, N.E. (2020). Monitorability Under Assumptions. In: Deshmukh, J., Ničković, D. (eds) Runtime Verification. RV 2020. Lecture Notes in Computer Science(), vol 12399. Springer, Cham. https://doi.org/10.1007/978-3-030-60508-7_1

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  • DOI: https://doi.org/10.1007/978-3-030-60508-7_1

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  • Online ISBN: 978-3-030-60508-7

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