Acculock: Accurate and efficient detection of data races

Abstract

Happens-before detectors are precise but can be too conservative to detect certain data races in repeated test runs as they are sensitive to thread interleaving. By making the opposite tradeoffs, lockset detectors can detect more races but are not precise (by reporting false positives). For both types of detectors, happens-before detectors run more slowly as they use expensive vector clocks. Existing hybrid race detectors (combining lockset and happens-before) alleviate some of the limitations in both analysis techniques at the cost of additional analysis overhead. Recently, due to FastTrack, epoch-based happens-before and lockset detectors now exhibit comparable performance. It is the time to rethink how to design a hybrid race detector to balance precision and coverage, by leveraging the lightweightness of epoch clocks. Acculock is the first such a solution. Acculock analyzes a program by reasoning about the subset of the happens-before relation observed with lock acquires and releases excluded, thereby reducing its sensitivity to thread interleaving. When such a weaker happens-before relation is violated, Acculock applies a new efficient lockset algorithm to enforce a lock-based synchronization discipline by distinguishing the locks protecting reads and writes. The key motivation behind is to ensure that Acculock can improve happens-before detectors by discovering also data races in alternate thread interleavings when analyzing one program execution while limiting false warnings thus incurred in a controlled manner. In addition, Acculock achieves these objectives by maintaining comparable performance as FastTrack, the fastest happens-before detector. All these properties of Acculock are validated and confirmed by comparing it against six other detectors, all implemented in Jikes RVM using 11 benchmark programs.