Learning I/O Automata

  • Fides Aarts
  • Frits Vaandrager
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6269)


Links are established between three widely used modeling frameworks for reactive systems: the ioco theory of Tretmans, the interface automata of De Alfaro and Henzinger, and Mealy machines. It is shown that, by exploiting these links, any tool for active learning of Mealy machines can be used for learning I/O automata that are deterministic and output determined. The main idea is to place a transducer in between the I/O automata teacher and the Mealy machine learner, which translates concepts from the world of I/O automata to the world of Mealy machines, and vice versa. The transducer comes equipped with an interface automaton that allows us to focus the learning process on those parts of the behavior that can effectively be tested and/or are of particular interest. The approach has been implemented on top of the LearnLib tool and has been applied successfully to three case studies.


Output Action Session Initiation Protocol Input Action Label Transition System Automaton Learning 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Aarts, F.: Inference and Abstraction of Communication Protocols. Master thesis, Radboud University Nijmegen and Uppsala University (November 2009)Google Scholar
  2. 2.
    Aarts, F., Schmaltz, J., Vaandrager, F.: Inference and abstraction of the biometric passport (May 2010)Google Scholar
  3. 3.
  4. 4.
    Alur, R., Henzinger, T., Kupferman, O., Vardi, M.: Alternating refinement relations. In: Sangiorgi, D., de Simone, R. (eds.) CONCUR 1998. LNCS, vol. 1466, pp. 163–178. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  5. 5.
    Angluin, D.: Learning regular sets from queries and counterexamples. Inf. Comput. 75(2), 87–106 (1987)zbMATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Berg, T., Grinchtein, O., Jonsson, B., Leucker, M., Raffelt, H., Steffen, B.: On the correspondence between conformance testing and regular inference. In: Cerioli, M. (ed.) FASE 2005. LNCS, vol. 3442, pp. 175–189. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  7. 7.
    BSI. Advanced security mechanisms for machine readable travel documents - extended access control (eac) - version 1.11. Technical Report TR-03110, German Federal Office for Information Security (BSI), Bonn, Germany (2008)Google Scholar
  8. 8.
    de Alfaro, L., Henzinger, T.: Interface automata. In: ESEC/FSE 2001. Software Engineering Notes, vol. 26, pp. 109–120. ACM Press, New York (2001)CrossRefGoogle Scholar
  9. 9.
    Henzinger, T.: Two challenges in embedded systems design: Predictability and robustness. Philosophical Trans. of the Royal Society A 366, 3727–3736 (2008)CrossRefGoogle Scholar
  10. 10.
    Higuera, C.d.: Grammatical Inference: Learning Automata and Grammars. Cambridge University Press, Cambridge (2010)zbMATHGoogle Scholar
  11. 11.
    Hungar, H., Niese, O., Steffen, B.: Domain-specific optimization in automata learning. In: Hunt Jr., W.A., Somenzi, F. (eds.) CAV 2003. LNCS, vol. 2725, pp. 315–327. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  12. 12.
    ICAO. Doc 9303 - machine readable travel documents - part 1-2. Technical report, International Civil Aviation Organization, 6th edn. (2006) Google Scholar
  13. 13.
    Jonsson, B.: Modular verification of asynchronous networks. In: PODC 1987, pp. 152–166 (1987)Google Scholar
  14. 14.
    Larsen, K., Nyman, U., Wasowski, A.: Modal i/o automata for interface and product line theories. In: De Nicola, R. (ed.) ESOP 2007. LNCS, vol. 4421, pp. 64–79. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  15. 15.
    Lee, D., Yannakakis, M.: Principles and methods of testing finite state machines — a survey. Proceedings of the IEEE 84(8), 1090–1123 (1996)CrossRefGoogle Scholar
  16. 16.
    Leucker, M.: Learning meets verification. In: de Boer, F.S., Bonsangue, M.M., Graf, S., de Roever, W.-P. (eds.) FMCO 2006. LNCS, vol. 4709, pp. 127–151. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  17. 17.
    Lynch, N.: Distributed Algorithms. Morgan Kaufmann Publishers, Inc., San Francisco (1996)zbMATHGoogle Scholar
  18. 18.
    Lynch, N., Tuttle, M.: Hierarchical correctness proofs for distributed algorithms. In: PODC 1987, pp. 137–151 (1987)Google Scholar
  19. 19.
    Mostowski, W., Poll, E., Schmaltz, J., Tretmans, J., Wichers Schreur, R.: Model-based testing of electronic passports. In: FMICS 2009, pp. 207–209. Springer, Heidelberg (2009)Google Scholar
  20. 20.
    Niese, O.: An Integrated Approach to Testing Complex Systems. PhD thesis, University of Dortmund (2003)Google Scholar
  21. 21.
    Panangaden, P., Stark, E.: Computations, residuals, and the power of indeterminancy. In: Lepistö, T., Salomaa, A. (eds.) ICALP 1988. LNCS, vol. 317, pp. 439–454. Springer, Heidelberg (1988)Google Scholar
  22. 22.
    Raffelt, H., Steffen, B., Berg, T.: Learnlib: a library for automata learning and experimentation. In: FMICS 2005, pp. 62–71. ACM Press, New York (2005)CrossRefGoogle Scholar
  23. 23.
    Raffelt, H., Steffen, B., Berg, T., Margaria, T.: Learnlib: a framework for extrapolating behavioral models. STTT 11(5), 393–407 (2009)CrossRefGoogle Scholar
  24. 24.
    Rosenberg, J., Schulzrinne, H.: Reliability of Provisional Responses in Session Initiation Protocol (SIP). RFC 3262 (Proposed Standard) (June 2002)Google Scholar
  25. 25.
    Rosenberg, J., Schulzrinne, H., Camarillo, G., Johnston, A., Peterson, J., Sparks, R., Handley, M., Schooler, E.: SIP: Session Initiation Protocol. RFC 3261 (Proposed Standard). Updated by RFCs 3265, 3853, 4320, 4916, 5393 (June 2002)Google Scholar
  26. 26.
    Tretmans, J.: Test generation with inputs, outputs, and repetitive quiescence. Software–Concepts and Tools 17, 103–120 (1996)zbMATHGoogle Scholar
  27. 27.
    Tretmans, J.: Model based testing with labelled transition systems. In: Hierons, R.M., Bowen, J.P., Harman, M. (eds.) FORTEST. LNCS, vol. 4949, pp. 1–38. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  28. 28.
    Veanes, M., Bjørner, N.: Input-output model programs. In: Leucker, M., Morgan, C. (eds.) Theoretical Aspects of Computing - ICTAC 2009. LNCS, vol. 5684, pp. 322–335. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  29. 29.
    Willemse, T.: Heuristics for ioco-based test-based modelling. In: Brim, L., Haverkort, B.R., Leucker, M., van de Pol, J. (eds.) FMICS 2006 and PDMC 2006. LNCS, vol. 4346, pp. 132–147. Springer, Heidelberg (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Fides Aarts
    • 1
  • Frits Vaandrager
    • 1
  1. 1.Institute for Computing and Information SciencesRadboud University NijmegenNijmegenThe Netherlands

Personalised recommendations