Probabilistic Program Verification via Inductive Synthesis of Inductive Invariants [article]

Kevin Batz, Mingshuai Chen, Sebastian Junges, Benjamin Lucien Kaminski, Joost-Pieter Katoen, Christoph Matheja
2022 arXiv   pre-print
A desired property of randomized systems, represented by probabilistic programs, is that the probability to reach some error state is sufficiently small; verification of such properties is often addressed by probabilistic model checking. We contribute an inductive synthesis approach for proving quantitative reachability properties by finding inductive invariants on source-code level. Our prototype implementation of various flavors of this approach shows promise: it finds inductive invariants
more » ... (in)finite-state programs, while beating state-of-the-art model checkers on some benchmarks and often outperforming monolithic alternatives.
arXiv:2205.06152v1 fatcat:fx27zel32bhfnkd24zj5ajrgpi