2019/05/26 by Martin Sulzmann, Sulzmann, Martin, Kai Stadtmüller +1
Computer Science · Decision Sciences · #Advanced Data Storage Technologies #Computer science #FOS: Computer and information sciences #Gender studies #Parallel Computing and Optimization Techniques #Programming Languages (cs.PL) #Race (biology) #Scientific Computing and Data Management #Sociology #cs.PL
paper · pdf · doi:10.48550/arxiv.1905.10855
published in arXiv (Cornell University) (Cornell University) · 26 pages with appendix
openalex publication_date 2019/05/26 · arxiv created 2019/10/26 · arxiv updated 2019/10/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Happens-before based data race prediction methods infer from a trace of events a partial order to check if one event happens before another event. If two two write events are unordered, they are in a race. We observe that common tracing methods provide no guarantee that the trace order corresponds to an actual program run. The consequence of inaccurate tracing is that results (races) reported are inaccurate. We introduce diagnostic methods to examine if (1) a race is guaranteed to be correct regardless of any potential inaccuracies, (2) maybe is incorrect due to inaccurate tracing. We have fully implemented the approach and provide for an empirical comparison with state of the art happens-before based race predictors such as FastTrack and SHB.