Probabilistic Program Verification via Inductive Synthesis of Inductive Invariants

Author:

Batz KevinORCID,Chen MingshuaiORCID,Junges SebastianORCID,Kaminski Benjamin LucienORCID,Katoen Joost-PieterORCID,Matheja ChristophORCID

Abstract

AbstractEssential 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.

Publisher

Springer Nature Switzerland

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Programmatic Strategy Synthesis: Resolving Nondeterminism in Probabilistic Programs;Proceedings of the ACM on Programming Languages;2024-01-05

2. Strong Invariants Are Hard: On the Hardness of Strongest Polynomial Invariants for (Probabilistic) Programs;Proceedings of the ACM on Programming Languages;2024-01-05

3. A Deductive Verification Infrastructure for Probabilistic Programs;Proceedings of the ACM on Programming Languages;2023-10-16

4. MDPs as Distribution Transformers: Affine Invariant Synthesis for Safety Objectives;Computer Aided Verification;2023

5. Probabilistic Program Verification via Inductive Synthesis of Inductive Invariants;Tools and Algorithms for the Construction and Analysis of Systems;2023

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