Abstract
Automata learning techniques are getting significant importance for their applications in a wide variety of software engineering problems, especially in the analysis and testing of complex systems. In recent studies, a previous learning approach [1] has been extended to synthesize Mealy machine models which are specifically tailored for I/O based systems. In this paper, we discuss the inference of Mealy machines and propose improvements that reduces the worst-time learning complexity of the existing algorithm. The gain over the complexity of the proposed algorithm has also been confirmed by experimentation on a large set of finite state machines.
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References
Angluin, D.: Learning regular sets from queries and counterexamples. Information and Computation 2, 87–106 (1987)
Muccini, H., Polini, A., Ricci, F., Bertolino, A.: Monitoring architectural properties in dynamic component-based systems. In: Schmidt, H.W., Crnković, I., Heineman, G.T., Stafford, J.A. (eds.) CBSE 2007. LNCS, vol. 4608, pp. 124–139. Springer, Heidelberg (2007)
Shu, G., Lee, D.: Testing security properties of protocol implementations-a machine learning based approach. In: ICDCS, p. 25. IEEE Computer Society, Los Alamitos (2007)
Peled, D., Vardi, M.Y., Yannakakis, M.: Black box checking. In: Proceedings of FORTE 1999, Beijing, China (1999)
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)
Margaria, T., Niese, O., Raffelt, H., Steffen, B.: Efficient test-based model generation for legacy reactive systems. In: HLDVT, pp. 95–100. IEEE Computer Society, Los Alamitos (2004)
Niese, O.: An Integrated Approach to Testing Complex Systems. PhD thesis, University of Dortmund (2003)
Mäkinen, E., Systä, T.: MAS - an interactive synthesizer to support behavioral modelling in UML. In: ICSE 2001, pp. 15–24. IEEE Computer Society, Los Alamitos (2001)
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)
Li, K., Groz, R., Shahbaz, M.: Integration testing of components guided by incremental state machine learning. In: TAIC PART, pp. 59–70. IEEE Computer Society, Los Alamitos (2006)
Pena, J.M., Oliveira, A.L.: A new algorithm for the reduction of incompletely specified finite state machines. In: ICCAD, pp. 482–489. ACM, New York (1998)
Frazier, M., Goldman, S., Mishra, N., Pitt, L.: Learning from a consistently ignorant teacher. J. Comput. Syst. Sci. 52(3), 471–492 (1996)
Shahbaz, M.: Reverse Engineering Enhanced State Models of Black Box Components to support Integration Testing. PhD thesis, Grenoble Universities (2008)
Rivest, R.L., Schapire, R.E.: Inference of finite automata using homing sequences. In: Machine Learning: From Theory to Applications, pp. 51–73 (1993)
Balcazar, J.L., Diaz, J., Gavalda, R.: Algorithms for learning finite automata from queries: A unified view. In: AALC, pp. 53–72 (1997)
Berg, T., Raffelt, H.: Model checking. In: Broy, M., Jonsson, B., Katoen, J.-P., Leucker, M., Pretschner, A. (eds.) Model-Based Testing of Reactive Systems. LNCS, vol. 3472, pp. 557–603. Springer, Heidelberg (2005)
Moller, F., Stevens, P.: Edinburgh Concurrency Workbench User Manual, Version 7.1 (2004), http://homepages.inf.ed.ac.uk/perdita/cwb/
Berg, T., Jonsson, B., Leucker, M., Saksena, M.: Insights to angluin’s learning. Electr. Notes Theor. Comput. Sci. 118, 3–18 (2005)
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Shahbaz, M., Groz, R. (2009). Inferring Mealy Machines. In: Cavalcanti, A., Dams, D.R. (eds) FM 2009: Formal Methods. FM 2009. Lecture Notes in Computer Science, vol 5850. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05089-3_14
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DOI: https://doi.org/10.1007/978-3-642-05089-3_14
Publisher Name: Springer, Berlin, Heidelberg
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