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Bounded Model Checking for Probabilistic Programs

Jansen, N; Dehnert, C; Kaminski, BL; Katoen, J-P; Westhofen, L; (2016) Bounded Model Checking for Probabilistic Programs. In: Artho, C and Legay, A and Peled, D, (eds.) Automated Technology for Verification and Analysis: 14th International Symposium, ATVA 2016, Chiba, Japan, October 17-20, 2016, Proceedings. (pp. pp. 68-85). Springer: Cham, Switzerland. Green open access

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Abstract

In this paper we investigate the applicability of standard model checking approaches to verifying properties in probabilistic programming. As the operational model for a standard probabilistic program is a potentially infinite parametric Markov decision process, no direct adaption of existing techniques is possible. Therefore, we propose an on–the–fly approach where the operational model is successively created and verified via a step–wise execution of the program. This approach enables to take key features of many probabilistic programs into account: nondeterminism and conditioning. We discuss the restrictions and demonstrate the scalability on several benchmarks.

Type: Proceedings paper
Title: Bounded Model Checking for Probabilistic Programs
Event: 14th International Symposium on Automated Technology for Verification and Analysis (ATVA)
Location: Chiba, JAPAN
Dates: 17 October 2016 - 20 October 2016
ISBN-13: 978-3-319-46519-7
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-319-46520-3_5
Publisher version: https://doi.org/10.1007/978-3-319-46520-3_5
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Model Check, Markov Decision Process, Operational Semantic, Program Variable, Probabilistic Program
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10089696
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