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32. Pastore, F., Micucci, D., Mariani, L.: Timed k-Tail: Automatic inference of timed automata.
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461
19. Farzan, A., Chen, Y., Clarke, E.M., Tsay, Y., Wang, B.: Extending automated compositional verification to the full class of omega-regular languages. In: Ramakrishnan, C.R.,
Rehof, J. (eds.) TACAS 2008. LNCS, vol. 4963, pp. 2–17. Springer, Heidelberg (2008).
https://doi.org/10.1007/978-3-540-78800-3 2
20. Fiterau-Brostean, P., Janssen, R., Vaandrager, F.W.: Combining model learning and
model checking to analyze TCP implementations. In: Chaudhuri, S., Farzan, A.
(eds.) CAV 2016. LNCS, vol. 9780, pp. 454–471. Springer, Heidelberg (2016).
https://doi.org/10.1007/978-3-319-41540-6 25
21. Fiterau-Brostean, P., Lenaerts, T., Poll, E., de Ruiter, J., Vaandrager, F.W., Verleg, P.: Model
learning and model checking of SSH implementations. In: Proceedings of the 24th ACM
SIGSOFT International SPIN Symposium on Model Checking of Software, SPIN 2017. pp.
142–151. ACM (2017)
22. Grinchtein, O., Jonsson, B., Leucker, M.: Learning of event-recording automata. Theor.
Comput. Sci. 411(47), 4029–4054 (2010)
23. Hopcroft, J.E., Ullman, J.D.: Introduction to Automata Theory, Languages, and Computation. Addison-Wesley Publishing Company (1979)
24. Howar, F., Jonsson, B., Vaandrager, F.W.: Combining black-box and white-box techniques
for learning register automata. In: Steffen, B., Woeginger, G.J. (eds.) Computing and Software Science - State of the Art and Perspectives, LNCS, vol. 10000, pp. 563–588. Springer,
Cham (2019). https://doi.org/10.1007/978-3-319-91908-9 26
25. Howar, F., Steffen, B., Jonsson, B., Cassel, S.: Inferring canonical register automata. In:
Kuncak, V., Rybalchenko, A. (eds.) VMCAI 2012. LNCS, vol. 7148, pp. 251–266. Springer,
Heidelberg (2012). https://doi.org/10.1007/978-3-642-27940-9 17
26. Information Science Institute, University of Southern California: Transmission control protocol (DARPA internet program protocol specification).
https://www.rfc-editor.org/rfc/rfc793.txt (1981)
27. Isberner, M., Howar, F., Steffen, B.: The open-source LearnLib - A framework for active
automata learning. In: Kroening, D., Pasareanu, C.S. (eds.) CAV 2015. LNCS, vol. 9206, pp.
487–495. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-319-21690-4 32
28. Li, Y., Chen, Y., Zhang, L., Liu, D.: A novel learning algorithm for B¨ uchi automata based on family of DFAs and classification trees. In: Legay, A., Margaria, T.
(eds.) TACAS 2017. LNCS, vol. 10205, pp. 208–226. Springer, Heidelberg (2017).
https://doi.org/10.1007/978-3-662-54577-5 12
29. Maler, O., Mens, I.: Learning regular languages over large alphabets. In: ´
Abrah´ am, E.,
Havelund, K. (eds.) TACAS 2014. LNCS, vol. 8413, pp. 485–499. Springer, Heidelberg
(2014). https://doi.org/10.1007/978-3-642-54862-8 41
30. Margaria, T., Niese, O., Raffelt, H., Steffen, B.: Efficient test-based model generation for
legacy reactive systems. In: Proceedings of the 9th IEEE International High-Level Design
Validation and Test Workshop, HLDVT 2004. pp. 95–100. IEEE Computer Society (2004)
31. Ouaknine, J., Worrell, J.: On the language inclusion problem for timed automata: Closing
a decidability gap. In: Proceedings of the 19th IEEE Symposium on Logic in Computer
Science, LICS 2004. pp. 54–63. IEEE Computer Society (2004)
32. Pastore, F., Micucci, D., Mariani, L.: Timed k-Tail: Automatic inference of timed automata.
In: Proceedings of 10th IEEE International Conference on Software Testing, Verification and
Validation, ICST 2017. pp. 401–411. IEEE Computer Society (2017)
33. Schmidt, J., Ghorbani, A., Hapfelmeier, A., Kramer, S.: Learning probabilistic real-time automata from multi-attribute event logs. Intell. Data Anal. 17(1), 93–123 (2013)
34. Shahbaz, M., Groz, R.: Inferring Mealy machines. In: Cavalcanti, A., Dams, D.
(eds.) FM 2009. LNCS, vol. 5850, pp. 207–222. Springer, Heidelberg (2009).
https://doi.org/10.1007/978-3-642-05089-3 14