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The TTT Algorithm: A Redundancy-Free Approach to Active Automata Learning

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Runtime Verification (RV 2014)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 8734))

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Abstract

In this paper we present TTT, a novel active automata learning algorithm formulated in the Minimally Adequate Teacher (MAT) framework. The distinguishing characteristic of TTT is its redundancy-free organization of observations, which can be exploited to achieve optimal (linear) space complexity. This is thanks to a thorough analysis of counterexamples, extracting and storing only the essential refining information. TTT is therefore particularly well-suited for application in a runtime verification context, where counterexamples (obtained, e.g., via monitoring) may be excessively long: as the execution time of a test sequence typically grows with its length, this would otherwise cause severe performance degradation. We illustrate the impact of TTT’s consequent redundancy-free approach along a number of examples.

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Isberner, M., Howar, F., Steffen, B. (2014). The TTT Algorithm: A Redundancy-Free Approach to Active Automata Learning. In: Bonakdarpour, B., Smolka, S.A. (eds) Runtime Verification. RV 2014. Lecture Notes in Computer Science, vol 8734. Springer, Cham. https://doi.org/10.1007/978-3-319-11164-3_26

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  • DOI: https://doi.org/10.1007/978-3-319-11164-3_26

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11163-6

  • Online ISBN: 978-3-319-11164-3

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