Abstract
This paper is concerned with bridging the gap between requirements, provided as a set of scenarios, and conforming design models. The novel aspect of our approach is to exploit learning for the synthesis of design models. In particular, we present a procedure that infers a message-passing automaton (MPA) from a given set of positive and negative scenarios of the system’s behavior provided as message sequence charts (MSCs). The paper investigates which classes of regular MSC languages and corresponding MPA can (not) be learned, and presents a dedicated tool based on the learning library LearnLib that supports our approach.
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Bollig, B., Katoen, JP., Kern, C., Leucker, M. (2007). Replaying Play In and Play Out: Synthesis of Design Models from Scenarios by Learning. In: Grumberg, O., Huth, M. (eds) Tools and Algorithms for the Construction and Analysis of Systems. TACAS 2007. Lecture Notes in Computer Science, vol 4424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71209-1_33
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DOI: https://doi.org/10.1007/978-3-540-71209-1_33
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