Introduction to Active Automata Learning from a Practical Perspective

Abstract : In this chapter we give an introduction to active learning of Mealy machines, an automata model particularly suited for modeling the behavior of realistic reactive systems. Active learning is characterized by its alternation of an exploration phase and a testing phase. During exploration phases so-called membership queries are used to construct hypothesis models of a system under learning. In testing phases so-called equivalence queries are used to compare respective hypothesis models to the actual system. These two phases are iterated until a valid model of the target system is produced. We will step-wisely elaborate on this simple algorithmic pattern, its underlying correctness arguments, its limitations, and, in particular, ways to overcome apparent hurdles for practical application. This should provide students and outsiders of the field with an intuitive account of the high potential of this challenging research area in particular concerning the control and validation of evolving reactive systems.
Type de document :
Communication dans un congrès
Formal Methods for Eternal Networked Software Systems, SFM 2011, Jun 2011, Bertinoro, Italy. Springer Verlag, 6659, pp.256-296, 2011, 〈http://www.springerlink.com/content/x32t376228601782/〉
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https://hal.inria.fr/hal-00647729
Contributeur : Falk Howar <>
Soumis le : vendredi 2 décembre 2011 - 15:29:41
Dernière modification le : vendredi 2 décembre 2011 - 15:49:23

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  • HAL Id : hal-00647729, version 1

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B. Steffen, F. Howar, M. Merten. Introduction to Active Automata Learning from a Practical Perspective. Formal Methods for Eternal Networked Software Systems, SFM 2011, Jun 2011, Bertinoro, Italy. Springer Verlag, 6659, pp.256-296, 2011, 〈http://www.springerlink.com/content/x32t376228601782/〉. 〈hal-00647729〉

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