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arXiv · 2205.06152

Probabilistic Program Verification via Inductive Synthesis of Inductive Invariants

Kevin Batz·Mingshuai Chen·Sebastian Junges·Benjamin Lucien Kaminski·Joost-Pieter Katoen·Christoph Matheja
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Abstract

Essential tasks for the verification of probabilistic programs include bounding expected outcomes and proving termination in finite expected runtime. We contribute a simple yet effective inductive synthesis approach for proving such quantitative reachability properties by generating inductive invariants on source-code level. Our implementation shows promise: It finds invariants for (in)finite-state programs, can beat state-of-the-art probabilistic model checkers, and is competitive with modern tools dedicated to invariant synthesis and expected runtime reasoning.

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Kevin Batz, Mingshuai Chen, Sebastian Junges, Benjamin Lucien Kaminski, Joost-Pieter Katoen, Christoph Matheja. 2022-05-12. Probabilistic Program Verification via Inductive Synthesis of Inductive Invariants. https://arxiv.org/abs/2205.06152

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