RDIT: race detection from incomplete traces

Abstract

We present RDIT, a novel dynamic algorithm to precisely detect data races in multi-threaded programs with incomplete trace information -- the presence of missing events. RDIT enhances the classical Happens-Before algorithm by relaxing the need to collect the full execution trace, while still guaranteeing full precision. The key idea behind RDIT is to abstract away the missing events by capturing the invocation data of the missing methods. This provides valuable information to approximate the possible synchronization behavior introduced by the missing events. By making the least conservative approximation that two missing methods introduce synchronization only when they access common data, RDIT guarantees to detect a maximal set of true races from the information available. We have conducted a preliminary study of RDIT on a real system and our results show that RDIT is promising; it detects no false positive when events are missed, whereas Happens-Before reports many.