Prinsys - On a quest for probabilistic loop invariants

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Abstract

Prinsys (pronounced "princess") is a new software-tool for probabilistic invariant synthesis. In this paper we discuss its implementation and improvements of the methodology which was set out in previous work. In particular we have substantially simplified the method and generalised it to non-linear programs and invariants. Prinsys follows a constraint-based approach. A given parameterised loop annotation is speculatively placed in the program. The tool returns a formula that captures precisely the invariant instances of the given candidate. Our approach is sound and complete. Prinsys's applicability is evaluated on several examples. We believe the tool contributes to the successful analysis of sequential probabilistic programs with infinite-domain variables and parameters. © 2013 Springer-Verlag.

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Gretz, F., Katoen, J. P., & McIver, A. (2013). Prinsys - On a quest for probabilistic loop invariants. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8054 LNCS, pp. 193–208). https://doi.org/10.1007/978-3-642-40196-1_17

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