Work

Soundness of Predictive Concurrency Analyses

Year: 2025

Type: article

Abstract: A predictive analysis takes an execution trace as input and discovers concurrency bugs without accessing the program source code. A sound predictive analysis reports no false positives, which sounds like a property that can be defined easily, but which has been defined in many different ways in previous work. In this paper, we unify, simplify, and generalize those soundness defInitions for analyses that discover concurrency bugs that can be represented as a consecutive sequence of events. Our soundness defInition is graph based, separates thread-local properties and whole-execution properties, and works well with weak memory executions. We also present a three-step proof recipe, and we use it to prove six existing analyses sound. This includes the first proof of soundness for a predictive analysis that works with weak memory.

Source: Proceedings of the ACM on Programming Languages

DOI: 10.1145/3720435

Authors: Shuyang Liu, Doug Lea, Jens Palsberg

Institutions: University of California, Los Angeles, State University of New York at Oswego

Language: English

Topic: Software Testing and Debugging Techniques

Subfield: Software

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funder: National Science Foundation

Award: SHF: Small: Concurrency with Specified Orders