Abstract
Model inference from system traces, e.g. for analysing legacy components or generating security tests for distributed components, is a common problem. Extended Finite State Machine (EFSM) models, managing an internal data state as a set of registers, are particularly well suited for capturing the behaviour of stateful components however existing inference techniques for (E)FSMs lack the ability to infer the internal state and its update functions.
In this paper, we present the underpinning formalism for an EFSM inference technique that involves the merging of transitions with updates to the internal data state. Our model is formalised in Isabelle/HOL, allowing for the machine-checked validation of transition merges and system properties.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Angluin, D.: Learning regular sets from queries and counterexamples. Inf. Comput. 75, 87–106 (1987). https://doi.org/10.1016/0890-5401(87)90052-6
Biermann, A.W., Feldman, J.A.: On the synthesis of finite-state machines from samples of their behavior. IEEE Trans. Comput. C-21(6), 592–597 (1972). https://doi.org/10.1109/TC.1972.5009015
Börger, E., Stärk, R.: Abstract State Machines. Springer, Heidelberg (2003). https://doi.org/10.1007/978-3-642-18216-7
Cheng, K.T., Krishnakumar, A.S.: Automatic functional test generation using the extended finite state machine model. In: International Design Automation Conference (DAC), pp. 86–91. ACM Press, New York (1993). https://doi.org/10.1145/157485.164585
Damas, C., Lambeau, B., Dupont, P., Van Lamsweerde, A.: Generating annotated behavior models from end-user scenarios. IEEE Trans. Softw. Eng. 31(12), 1056–1073 (2005). https://doi.org/10.1109/TSE.2005.138
Derrick, J., Boiten, E.A.: Refinement in Z and Object-Z, 2nd edn. Springer, London (2014). https://doi.org/10.1007/978-1-4471-5355-9
Dupont, P., Lambeau, B., Damas, C., Van Lamsweerde, A.: The QSM algorithm and its application to software behavior model induction. Appl. Artif. Intell. 22(1–2), 77–115 (2008). https://doi.org/10.1080/08839510701853200
Eilenberg, S.: Automata, Languages, and Machines. Academic Press Inc., Orlando (1974)
Ernst, M.D., Cockrell, J., Griswold, W.G., Notkin, D.: Dynamically discovering likely program invariants to support program evolution. IEEE Trans. Softw. Eng. 27(2), 99–123 (2001). https://doi.org/10.1109/32.908957
Fraser, G., Walkinshaw, N.: Behaviourally adequate software testing. In: International Conference on Software Testing, Verification and Validation, pp. 300–309, April 2012. https://doi.org/10.1109/ICST.2012.110
Gold, E.M.: Language identification in the limit. Inf. Control 10(5), 447–474 (1967)
Isberner, M., Howar, F., Steffen, B.: The TTT algorithm: a redundancy-free approach to active automata learning. In: Bonakdarpour, B., Smolka, S.A. (eds.) RV 2014. LNCS, vol. 8734, pp. 307–322. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11164-3_26
Lang, K.J., Pearlmutter, B.A., Price, R.A.: Results of the Abbadingo one DFA learning competition and a new evidence-driven state merging algorithm. In: Honavar, V., Slutzki, G. (eds.) ICGI 1998. LNCS, vol. 1433, pp. 1–12. Springer, Heidelberg (1998). https://doi.org/10.1007/BFb0054059
Lorenzoli, D., Mariani, L., Pezzè, M.: Inferring state-based behavior models. In: International Workshop on Dynamic Systems Analysis (WODA), p. 25. ACM Press, New York (2006). https://doi.org/10.1145/1138912.1138919
Lorenzoli, D., Mariani, L., Pezzè, M.: Automatic generation of software behavioral models. In: International Conference on Software Engineering (ICSE), p. 501. ACM Press, New York (2008). https://doi.org/10.1145/1368088.1368157
Nipkow, T., Wenzel, M., Paulson, L.C. (eds.): Isabelle/HOL. LNCS, vol. 2283. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-45949-9
Petrenko, A., Boroday, S., Groz, R.: Confirming configurations in EFSM testing. IEEE Trans. Softw. Eng. 30(1), 29–42 (2004). https://doi.org/10.1109/TSE.2004.1265734
Walkinshaw, N., Lambeau, B., Damas, C., Bogdanov, K., Dupont, P.: STAMINA: a competition to encourage the development and assessment of software model inference techniques. Empir. Softw. Eng. 18(4), 791–824 (2013). https://doi.org/10.1007/s10664-012-9210-3
Walkinshaw, N., Taylor, R., Derrick, J.: Inferring extended finite state machine models from software executions. Empir. Softw. Eng. 21(3), 811–853 (2016). https://doi.org/10.1007/s10664-015-9367-7
Weyuker, E.J.: Assessing test data adequacy through program inference. ACM Trans. Program. Lang. Syst. 5(4), 641–655 (1983)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Foster, M., Taylor, R.G., Brucker, A.D., Derrick, J. (2018). Formalising Extended Finite State Machine Transition Merging. In: Sun, J., Sun, M. (eds) Formal Methods and Software Engineering. ICFEM 2018. Lecture Notes in Computer Science(), vol 11232. Springer, Cham. https://doi.org/10.1007/978-3-030-02450-5_22
Download citation
DOI: https://doi.org/10.1007/978-3-030-02450-5_22
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-02449-9
Online ISBN: 978-3-030-02450-5
eBook Packages: Computer ScienceComputer Science (R0)