Publication details
On Lexicographic Proof Rules for Probabilistic Termination
| Authors | |
|---|---|
| Year of publication | 2023 |
| Type | Peer-reviewed scientific article |
| Magazine / Source | Formal Aspects of Computing |
| MU Faculty or unit | |
| Citation | |
| web | https://dl.acm.org/doi/10.1145/3585391 |
| Doi | https://doi.org/10.1145/3585391 |
| Keywords | probabilistic programs; termination; martingales |
| Description | We consider the almost-sure (a.s.) termination problem for probabilistic programs, which are a stochastic extension of classical imperative programs. Lexicographic ranking functions provide a sound and practical approach for termination of non-probabilistic programs, and their extension to probabilistic programs is achieved via lexicographic ranking supermartingales (LexRSMs). However, LexRSMs introduced in the previous work have a limitation that impedes their automation: all of their components have to be non-negative in all reachable states. This might result in a LexRSM not existing even for simple terminating programs. Our contributions are twofold. First, we introduce a generalization of LexRSMs that allows for some components to be negative. This standard feature of non-probabilistic termination proofs was hitherto not known to be sound in the probabilistic setting, as the soundness proof requires a careful analysis of the underlying stochastic process. Second, we present polynomial-time algorithms using our generalized LexRSMs for proving a.s. termination in broad classes of linear-arithmetic programs. |
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