Details

Autor(en) / Beteiligte

• Abdulla, Parosh
• Atig, Mohamed Faouzi
• Agarwal, Raj Aryan
• Godbole, Adwait
• Krishna, S.

Titel

Probabilistic Total Store Ordering

Ist Teil von

• Programming Languages And Systems, ESOP 2022, 2022, p.317

Erscheinungsjahr

2022

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• We present Probabilistic Total Store Ordering (PTSO) - a probabilistic extension of the classical TSO semantics. For a given (finite-state) program, the operational semantics of PTSO induces an infinite-state Markov chain. We resolve the inherent non-determinism due to process schedulings and memory updates according to given probability distributions. We provide a comprehensive set of results showing the decidability of several properties for PTSO, namely (i) Almost-Sure (Repeated) Reachability: whether a run, starting from a given initial configuration, almost surely visits (resp. almost surely repeatedly visits) a given set of target configurations. (ii) Almost-Never (Repeated) Reachability: whether a run from the initial configuration, almost never visits (resp. almost never repeatedly visits) the target. (iii) Approximate Quantitative (Repeated) Reachability: to approximate, up to an arbitrary degree of precision, the measure of runs that start from the initial configuration and (repeatedly) visit the target. (iv) Expected Average Cost: to approximate, up to an arbitrary degree of precision, the expected average cost of a run from the initial configuration to the target. We derive our results through a nontrivial combination of results from the classical theory of (infinite-state) Markov chains, the theories of decisive and eager Markov chains, specific techniques from combinatorics, as well as, decidability and complexity results for the classical (non-probabilistic) TSO semantics. As far as we know, this is the first work that considers probabilistic verification of programs running on weak memory models.