A Foundation for Runtime Monitoring

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10548)


Runtime Verification is a lightweight technique that complements other verification methods in an effort to ensure software correctness. The technique poses novel questions to software engineers: it is not easy to identify which specifications are amenable to runtime monitoring, nor is it clear which monitors effect the required runtime analysis correctly. This exposition targets a foundational understanding of these questions. Particularly, it considers an expressive specification logic (a syntactic variant of the modal \(\mu \)-calculus) that is agnostic of the verification method used, together with an elemental framework providing an operational semantics for the runtime analysis performed by monitors. The correspondence between the property satisfactions in the logic on the one hand, and the verdicts reached by the monitors performing the analysis on the other, is a central theme of the study. Such a correspondence underpins the concept of monitorability, used to identify the subsets of the logic that can be adequately monitored for by RV. Another theme of the study is that of understanding what should be expected of a monitor in order for the verification process to be correct. We show how the monitor framework considered can constitute a basis whereby various notions of monitor correctness may be defined and investigated.


  1. 1.
    Aceto, L., Achilleos, A., Francalanza, A., Ingólfsdóttir, A., Kjartansson, S.Ö.: On the complexity of determinizing monitors. In: Carayol, A., Nicaud, C. (eds.) CIAA 2017. LNCS, vol. 10329, pp. 1–13. Springer, Cham (2017). doi: 10.1007/978-3-319-60134-2_1 CrossRefGoogle Scholar
  2. 2.
    Aceto, L., Ingólfsdóttir, A., Larsen, K.G., Srba, J.: Reactive Systems: Modelling, Specification and Verification. Cambridge University Press, Cambridge (2007)CrossRefzbMATHGoogle Scholar
  3. 3.
    Ahrendt, W., Chimento, J.M., Pace, G.J., Schneider, G.: A specification language for static and runtime verification of data and control properties. In: Bjørner, N., de Boer, F. (eds.) FM 2015. LNCS, vol. 9109, pp. 108–125. Springer, Cham (2015). doi: 10.1007/978-3-319-19249-9_8 CrossRefGoogle Scholar
  4. 4.
    Aktug, I., Naliuka, K.: ConSpec - a formal language for policy specification. Sci. Comput. Program. 74(1–2), 2–12 (2008)MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    Artho, C., Barringer, H., Goldberg, A., Havelund, K., Khurshid, S., Lowry, M.R., Pasareanu, C.S., Rosu, G., Sen, K., Visser, W., Washington, R.: Combining test case generation and runtime verification. Theor. Comput. Sci. 336(2–3), 209–234 (2005)MathSciNetCrossRefzbMATHGoogle Scholar
  6. 6.
    Attard, D.P., Francalanza, A.: A monitoring tool for a branching-time logic. In: Falcone, Y., Sánchez, C. (eds.) RV 2016. LNCS, vol. 10012, pp. 473–481. Springer, Cham (2016). doi: 10.1007/978-3-319-46982-9_31 CrossRefGoogle Scholar
  7. 7.
    Attard, D.P., Francalanza, A.: Trace partitioning and local monitoring for asynchronous components. In: SEFM, LNCS (2017, to appear)Google Scholar
  8. 8.
    Azzopardi, S., Colombo, C., Pace, G.J., Vella, B.: Compliance checking in the open payments ecosystem. In: De Nicola, R., Kühn, E. (eds.) SEFM 2016. LNCS, vol. 9763, pp. 337–343. Springer, Cham (2016). doi: 10.1007/978-3-319-41591-8_23 Google Scholar
  9. 9.
    Baier, C., Katoen, J.P.: Principles of Model Checking. MIT Press, New York (2008)zbMATHGoogle Scholar
  10. 10.
    Barringer, H., Goldberg, A., Havelund, K., Sen, K.: Rule-based runtime verification. In: Steffen, B., Levi, G. (eds.) VMCAI 2004. LNCS, vol. 2937, pp. 44–57. Springer, Heidelberg (2004). doi: 10.1007/978-3-540-24622-0_5 CrossRefGoogle Scholar
  11. 11.
    Basin, D., Klaedtke, F., Marinovic, S., Zălinescu, E.: Monitoring compliance policies over incomplete and disagreeing logs. In: Qadeer, S., Tasiran, S. (eds.) RV 2012. LNCS, vol. 7687, pp. 151–167. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-35632-2_17 CrossRefGoogle Scholar
  12. 12.
    Brat, G.P., Drusinsky, D., Giannakopoulou, D., Goldberg, A., Havelund, K., Lowry, M.R., Pasareanu, C.S., Venet, A., Visser, W., Washington, R.: Experimental evaluation of verification and validation tools on martian rover software. Formal Methods Syst. Des. 25(2–3), 167–198 (2004)CrossRefzbMATHGoogle Scholar
  13. 13.
    Cassar, I., Francalanza, A.: Runtime adaptation for actor systems. In: Bartocci, E., Majumdar, R. (eds.) RV 2015. LNCS, vol. 9333, pp. 38–54. Springer, Cham (2015). doi: 10.1007/978-3-319-23820-3_3 CrossRefGoogle Scholar
  14. 14.
    Cassar, I., Francalanza, A.: On implementing a monitor-oriented programming framework for actor systems. In: Ábrahám, E., Huisman, M. (eds.) IFM 2016. LNCS, vol. 9681, pp. 176–192. Springer, Cham (2016). doi: 10.1007/978-3-319-33693-0_12 CrossRefGoogle Scholar
  15. 15.
    Cassar, I., Francalanza, A., Aceto, L., Ingólfsdóttir, A.: eAOP - an aspect oriented programming framework for erlang. In: Erlang Workshop (2017, to appear)Google Scholar
  16. 16.
    Chen, F., Rosu, G.: MOP: an efficient and generic runtime verification framework. In: OOPSLA, pp. 569–588 (2007)Google Scholar
  17. 17.
    Clarke, E.M., Grumberg, O., Peled, D.A.: Model Checking. MIT Press, Cambridge (1999)Google Scholar
  18. 18.
    Colombo, C., Francalanza, A., Mizzi, R., Pace, G.J.: polyLarva: runtime verification with configurable resource-aware monitoring boundaries. In: Eleftherakis, G., Hinchey, M., Holcombe, M. (eds.) SEFM 2012. LNCS, vol. 7504, pp. 218–232. Springer, Heidelberg (2012). doi: 10.1007/978-3-642-33826-7_15 CrossRefGoogle Scholar
  19. 19.
    D’Angelo, B., Sankaranarayanan, S., Sánchez, C., Robinson, W., Finkbeiner, B., Sipma, H.B., Mehrotra, S., Manna, Z.: LOLA: runtime monitoring of synchronous systems. In: TIME, pp. 166–174 (2005)Google Scholar
  20. 20.
    Debois, S., Hildebrandt, T., Slaats, T.: Safety, liveness and run-time refinement for modular process-aware information systems with dynamic sub processes. In: Bjørner, N., de Boer, F. (eds.) FM 2015. LNCS, vol. 9109, pp. 143–160. Springer, Cham (2015). doi: 10.1007/978-3-319-19249-9_10 CrossRefGoogle Scholar
  21. 21.
    Decker, N., Leucker, M., Thoma, D.: jUnitRV–adding runtime verification to jUnit. In: Brat, G., Rungta, N., Venet, A. (eds.) NFM 2013. LNCS, vol. 7871, pp. 459–464. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-38088-4_34 CrossRefGoogle Scholar
  22. 22.
    Monica, D.D., Francalanza, A.: Towards a hybrid approach to software verification. In: NWPT, number SCS16001 in RUTR, pp. 51–54 (2015)Google Scholar
  23. 23.
    Francalanza, A.: A theory of monitors. In: Jacobs, B., Löding, C. (eds.) FoSSaCS 2016. LNCS, vol. 9634, pp. 145–161. Springer, Heidelberg (2016). doi: 10.1007/978-3-662-49630-5_9 CrossRefGoogle Scholar
  24. 24.
    Francalanza, A.: Consistently-detecting monitors. In: CONCUR. Dagstuhl Publishing (LIPICS) (2017)Google Scholar
  25. 25.
    Francalanza, A., Aceto, L., Ingolfsdottir, A.: On verifying hennessy-milner logic with recursion at runtime. In: Bartocci, E., Majumdar, R. (eds.) RV 2015. LNCS, vol. 9333, pp. 71–86. Springer, Cham (2015). doi: 10.1007/978-3-319-23820-3_5 CrossRefGoogle Scholar
  26. 26.
    Francalanza, A., Aceto, L., Ingolfsdottir, A.: Monitorability for the hennessy-milner logic with recursion. Formal Methods Syst. Des., 1–30 (2017)Google Scholar
  27. 27.
    Francalanza, A., Seychell, A.: Synthesising correct concurrent runtime monitors. Formal Methods Syst. Des. 46(3), 226–261 (2015)CrossRefzbMATHGoogle Scholar
  28. 28.
    Kane, A., Chowdhury, O., Datta, A., Koopman, P.: A case study on runtime monitoring of an autonomous research vehicle (ARV) system. In: Bartocci, E., Majumdar, R. (eds.) RV 2015. LNCS, vol. 9333, pp. 102–117. Springer, Cham (2015). doi: 10.1007/978-3-319-23820-3_7 CrossRefGoogle Scholar
  29. 29.
    Kassem, A., Falcone, Y., Lafourcade, P.: Monitoring electronic exams. In: Bartocci, E., Majumdar, R. (eds.) RV 2015. LNCS, vol. 9333, pp. 118–135. Springer, Cham (2015). doi: 10.1007/978-3-319-23820-3_8 CrossRefGoogle Scholar
  30. 30.
    Kim, M., Viswanathan, M., Kannan, S., Lee, I., Sokolsky, O.: Java-MaC: a run-time assurance approach for Java programs. Formal Methods Syst. Des. 24(2), 129–155 (2004)CrossRefzbMATHGoogle Scholar
  31. 31.
    Klamka, J.: system characteristics: stability, controllability, observability. In: Control System, Robotics and Automation, EOLLS, vol. 7 (2009)Google Scholar
  32. 32.
    Kozen, D.: Results on the propositional \(\upmu \)-calculus. Theor. Comput. Sci. 27, 333–354 (1983)MathSciNetCrossRefzbMATHGoogle Scholar
  33. 33.
    Larsen, K.G.: Proof systems for satisfiability in hennessy-milner logic with recursion. Theor. Comput. Sci. 72(2&3), 265–288 (1990)MathSciNetCrossRefzbMATHGoogle Scholar
  34. 34.
    Lerda, F., Visser, W.: Addressing dynamic issues of program model checking. In: Dwyer, M. (ed.) SPIN 2001. LNCS, vol. 2057, pp. 80–102. Springer, Heidelberg (2001). doi: 10.1007/3-540-45139-0_6 CrossRefGoogle Scholar
  35. 35.
    Leucker, M., Schallhart, C.: A brief account of runtime verification. J. Log. Algebr. Program. 78(5), 293–303 (2009)CrossRefzbMATHGoogle Scholar
  36. 36.
    Ligatti, J., Bauer, L., Walker, D.: Edit automata: enforcement mechanisms for run-time security policies. Int. J. Inf. Secur. 4(1–2), 2–16 (2005)CrossRefGoogle Scholar
  37. 37.
    Meredith, P.O., Jin, D., Griffith, D., Chen, F., Rosu, G.: An overview of the MOP runtime verification framework. STTT 14(3), 249–289 (2012)CrossRefGoogle Scholar
  38. 38.
    Neykova, R., Yoshida, N.: Let it recover: multiparty protocol-induced recovery. In: CC, pp. 98–108 (2017)Google Scholar
  39. 39.
    Reger, G., Cruz, H.C., Rydeheard, D.: MarQ: monitoring at runtime with QEA. In: Baier, C., Tinelli, C. (eds.) TACAS 2015. LNCS, vol. 9035, pp. 596–610. Springer, Heidelberg (2015). doi: 10.1007/978-3-662-46681-0_55 Google Scholar
  40. 40.
    Varvaressos, S., Vaillancourt, D., Gaboury, S., Blondin Massé, A., Hallé, S.: Runtime monitoring of temporal logic properties in a platform game. In: Legay, A., Bensalem, S. (eds.) RV 2013. LNCS, vol. 8174, pp. 346–351. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-40787-1_23 CrossRefGoogle Scholar

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© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of MaltaMsidaMalta
  2. 2.School of Computer ScienceReykjavík UniversityReykjavikIceland
  3. 3.Departamento de Sistemas Informáticos y ComputaciónUniversidad Complutense de MadridMadridSpain
  4. 4.Dipartimento di Ingegneria Elettrica e Tecnologie dell’InformazioneUniversità “Federico II” di NapoliNaplesItaly

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