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.
@article{arxiv.2205.06152,
title = {Probabilistic Program Verification via Inductive Synthesis of Inductive Invariants},
author = {Kevin Batz and Mingshuai Chen and Sebastian Junges and Benjamin Lucien Kaminski and Joost-Pieter Katoen and Christoph Matheja},
journal= {arXiv preprint arXiv:2205.06152},
year = {2023}
}