Dimitrova, R., Ferrer Fioriti, L.M., Hermanns, H. et al. (1 more author) (2016) Probabilistic CTL* : the deductive way. In: Chechik, M. and Raskin, J.-F., (eds.) Tools and Algorithms for the Construction and Analysis of Systems - 22nd International Conference, TACAS 2016. Tools and Algorithms for the Construction and Analysis of Systems, 02-08 Apr 2016, Eindhoven, The Netherlands. Lecture Notes in Computer Science (9636). Springer , pp. 280-296. ISBN 9783662496732
Abstract
Complex probabilistic temporal behaviours need to be guaranteed in robotics and various other control domains, as well as in the context of families of randomized protocols. At its core, this entails checking infinite-state probabilistic systems with respect to quantitative properties specified in probabilistic temporal logics. Model checking methods are not directly applicable to infinite-state systems, and techniques for infinite-state probabilistic systems are limited in terms of the specifications they can handle.
This paper presents a deductive approach to the verification of countable-state systems against properties specified in probabilistic CTL ∗ , on models featuring both nondeterministic and probabilistic choices. The deductive proof system we propose lifts the classical proof system by Kesten and Pnueli to the probabilistic setting. However, the soundness arguments are completely distinct and go via the theory of martingales. Completeness results for the finite-state case and an infinite-state example illustrate the effectiveness of our approach.
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: | © 2016 Springer-Verlag. This is an author-produced version of a paper subsequently published in TACAS 2016. 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 12:28 |
Last Modified: | 05 Feb 2020 15:47 |
Status: | Published |
Publisher: | Springer |
Series Name: | Lecture Notes in Computer Science |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-662-49674-9_16 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:156432 |