Probabilistic Termination

Author:

Ferrer Fioriti Luis María1,Hermanns Holger1

Affiliation:

1. Saarland University, Saarbrucken, Germany

Abstract

We propose a framework to prove almost sure termination for probabilistic programs with real valued variables. It is based on ranking supermartingales, a notion analogous to ranking functions on non-probabilistic programs. The framework is proven sound and complete for a meaningful class of programs involving randomization and bounded nondeterminism. We complement this foundational insigh by a practical proof methodology, based on sound conditions that enable compositional reasoning and are amenable to a direct implementation using modern theorem provers. This is integrated in a small dependent type system, to overcome the problem that lexicographic ranking functions fail when combined with randomization. Among others, this compositional methodology enables the verification of probabilistic programs outside the complete class that admits ranking supermartingales.

Funder

Seventh Framework Programme

Deutsche Forschungsgemeinschaft

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Software

Cited by 23 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. Stochastic Omega-Regular Verification and Control with Supermartingales;Lecture Notes in Computer Science;2024

2. Omnisemantics: Smooth Handling of Nondeterminism;ACM Transactions on Programming Languages and Systems;2023-03-08

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

4. Learning Probabilistic Termination Proofs;Computer Aided Verification;2021

5. Proving almost-sure termination by omega-regular decomposition;Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation;2020-06-06

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