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arXiv · 1605.04477

Bounded Model Checking for Probabilistic Programs

Nils Jansen·Christian Dehnert·Benjamin Lucien Kaminski·Joost-Pieter Katoen·Lukas Westhofen
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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.

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Nils Jansen, Christian Dehnert, Benjamin Lucien Kaminski, Joost-Pieter Katoen, Lukas Westhofen. 2016-07-26. Bounded Model Checking for Probabilistic Programs. https://arxiv.org/abs/1605.04477

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