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nfer – A Notation and System for Inferring Event Stream Abstractions

  • Sean Kauffman
  • Klaus HavelundEmail author
  • Rajeev Joshi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10012)

Abstract

We propose a notation for specifying event stream abstractions for use in spacecraft telemetry processing. Our work is motivated by the need to quickly process streams with millions of events generated by the Curiosity rover on Mars. The approach builds a hierarchy of event abstractions for telemetry visualization and querying to aid human comprehension. Such abstractions can also be used as input to other runtime verification tools. Our notation is inspired by Allen’s Temporal Logic, and provides a rule-based declarative way to express event abstractions. The system is written in Scala, with the specification language implemented as an internal DSL. It is based on parallel executing actors communicating via a publish-subscribe model. We illustrate the solution with several examples, including a real telemetry analysis scenario.

References

  1. 1.
    Albarghouthi, A., Baier, J.A., McIlraith, S.A.: On the use of planning technology for verification. In: Proceedings of the ICAPS Workshop on Verification and Validation of Planning and Scheduling Systems (VVPS). Citeseer (2009)Google Scholar
  2. 2.
    Allen, J.F.: Maintaining knowledge about temporal intervals. Commun. ACM 26(11), 832–843 (1983)CrossRefzbMATHGoogle Scholar
  3. 3.
    Allen, J.F.: Towards a general theory of action and time. Artif. Intell. 23(2), 123–154 (1984)CrossRefzbMATHGoogle Scholar
  4. 4.
    Alur, R., Fisman, D., Raghothaman, M.: Regular programming for quantitative properties of data streams. In: Thiemann, P. (ed.) ESOP 2016. LNCS, vol. 9632, pp. 15–40. Springer, Heidelberg (2016). doi: 10.1007/978-3-662-49498-1_2 CrossRefGoogle Scholar
  5. 5.
    Basin, D., Harvan, M., Klaedtke, F., Zălinescu, E.: MONPOLY: monitoring usage-control policies. In: Khurshid, S., Sen, K. (eds.) RV 2011. LNCS, vol. 7186, pp. 360–364. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  6. 6.
    Bauer, A., Leucker, M., Schallhart, C.: The good, the bad, and the ugly, but how ugly is ugly? In: Sokolsky, O., Taşıran, S. (eds.) RV 2007. LNCS, vol. 4839, pp. 126–138. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  7. 7.
    Butler, R.W., Siminiceanu, R.I., Muno, C.: The ANMLite language and logic for specifying planning problems. Report No. 215088, 23681–2199 (2007)Google Scholar
  8. 8.
    Chen, F., Roşu, G.: MOP: an efficient and generic runtime verification framework. In: ACM SIGPLAN Notices, vol. 42, pp. 569–588. ACM (2007)Google Scholar
  9. 9.
    Dillon, L.K., Kutty, G., Moser, L.E., Melliar-Smith, P.M., Ramakrishna, Y.S.: A graphical interval logic for specifying concurrent systems. ACM Trans. Softw. Eng. Methodol. 3, 131–165 (1994)CrossRefzbMATHGoogle Scholar
  10. 10.
    Ernst, M.D., Perkins, J.H., Guo, P.J., McCamant, S., Pacheco, C., Tschantz, M.S., Xiao, C.: The Daikon system for dynamic detection of likely invariants. Sci. Comput. Program. 69(1), 35–45 (2007)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Finkbeiner, B., Sankaranarayanan, S., Sipma, H.: Collecting statistics over runtime executions. Formal Meth. Syst. Des. 27(3), 253–274 (2005)CrossRefzbMATHGoogle Scholar
  12. 12.
    Hansen, M.R., Van Hung, D.: A theory of duration calculus with application. In: George, C.W., Liu, Z., Woodcock, J. (eds.) Domaine Modeling. LNCS, vol. 4710, pp. 119–176. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  13. 13.
    Havelund, K.: Rule-based runtime verification revisited. Softw. Tools Technol. Transf. (STTT) 17, 143–170 (2015)CrossRefGoogle Scholar
  14. 14.
    Havelund, K., Joshi, R.: Comprehension of spacecraft telemetry using hierarchical specifications of behavior. In: Merz, S., Pang, J. (eds.) ICFEM 2014. LNCS, vol. 8829, pp. 187–202. Springer, Heidelberg (2014)Google Scholar
  15. 15.
    Havelund, K., Joshi, R.: Experience with rule-based analysis of spacecraft logs. In: Artho, C., Ölveczky, P.C. (eds.) FTSCS 2014. CCIS, vol. 476, pp. 1–16. Springer, Heidelberg (2015)Google Scholar
  16. 16.
    Kreps, J., Narkhede, N., Rao, J.: Kafka: a distributed messaging system for log processing. In: Proceedings of the 6th International Workshop on Networking Meets Databases (NetDB 2011), pp. 1–7. ACM (2011)Google Scholar
  17. 17.
    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)CrossRefGoogle Scholar
  18. 18.
    McDermott, D., Ghallab, M., Howe, A., Knoblock, C., Ram, A., Veloso, M., Weld, D., Wilkins, D.: PDDL-the planning domain definition language (1998)Google Scholar
  19. 19.
    Moszkowski, B.C.: A temporal logic for multilevel reasoning about hardware. IEEE Comput. 18, 10–19 (1985)CrossRefGoogle Scholar
  20. 20.
    Roşu, G., Bensalem, S.: Allen linear (interval) temporal logic–translation to LTL and monitor synthesis. In: Ball, T., Jones, R.B. (eds.) CAV 2006. LNCS, vol. 4144, pp. 263–277. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  21. 21.
    Shoham, S., Yahav, E., Fink, S.J., Pistoia, M.: Static specification mining using automata-based abstractions. IEEE Trans. Softw. Eng. 34(5), 651–666 (2008)CrossRefGoogle Scholar
  22. 22.
    Siminiceanu, R.I., Butler, R.W., Muñoz, C.A.: Experimental evaluation of a planning language suitable for formal verification. In: Peled, D.A., Wooldridge, M.J. (eds.) MoChArt 2008. LNCS, vol. 5348, pp. 132–146. Springer, Heidelberg (2009)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.University of WaterlooWaterlooCanada
  2. 2.Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaUSA

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