# Probabilistic Program Verification via Inductive Synthesis of Inductive Invariants

arXiv: https://arxiv.org/abs/2205.06152 · HTML: https://mlsanity.com/paper/2205.06152/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 May 2022.

## Built on by (most cited first, 2 of 2)

- [Quantitative Verification of Omega-regular Properties in Probabilistic Programming](https://mlsanity.com/paper/2512.21596/) (2025)
- [Entropy Objectives in Markov Decision Processes](https://mlsanity.com/paper/2606.21726/) (2026)

## Abstract (arXiv)

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.