Dimitrova, R., Finkbeiner, B. and Torfah, H. (2019) Approximate automata for omega-regular languages. In: Chen, Y.-F., Cheng, C.-H. and Esparza, J., (eds.) Automated Technology for Verification and Analysis - 17th International Symposium, ATVA 2019. Automated Technology for Verification and Analysis, 28-31 Oct 2019, Taipei, Taiwan. Lecture Notes in Computer Science (11781). Springer , pp. 334-349. ISBN 9783030317836
Abstract
Automata over infinite words, also known as ω -automata, play a key role in the verification and synthesis of reactive systems. The spectrum of ω -automata is defined by two characteristics: the acceptance condition (e.g. Büchi or parity) and the determinism (e.g., deterministic or nondeterministic) of an automaton. These characteristics play a crucial role in applications of automata theory. For example, certain acceptance conditions can be handled more efficiently than others by dedicated tools and algorithms. Furthermore, some applications, such as synthesis and probabilistic model checking, require that properties are represented as some type of deterministic ω -automata. However, properties cannot always be represented by automata with the desired acceptance condition and determinism.
In this paper we study the problem of approximating linear-time properties by automata in a given class. Our approximation is based on preserving the language up to a user-defined precision given in terms of the size of the finite lasso representation of infinite executions that are preserved. We study the state complexity of different types of approximating automata, and provide constructions for the approximation within different automata classes, for example, for approximating a given automaton by one with a simpler acceptance condition.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2019 Springer Nature. This is an author-produced version of a paper subsequently published in ATVA 2019. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 04 Feb 2020 11:34 |
Last Modified: | 21 Oct 2020 00:39 |
Status: | Published |
Publisher: | Springer |
Series Name: | Lecture Notes in Computer Science |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-030-31784-3_19 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:156422 |