ATDetector: ImprovingtheAccuracyofaCommercialData RaceDetectorbyIdentifyingAddressTransfer

In order to take advantage of multi-core hardware, more and more applications are becoming multi-threaded. Unfortunately concurrent programs are prone to bugs, such as data races. Recently much work has been devoted to detecting data races in multi-threaded programs. Most tools, however, require the accurate knowledge of synchronizations in the program, and may otherwise suffer from false positives in race detection, limiting their usability. To address this problem, some tools such as Intel R Inspector provide mechanisms for suppressing false positives and/or annotating synchronizations not automatically recognized by the tools. However, they require users’ input or even changes of the source code. We took a different approach to address this problem. More specifically, we first used a state-of-the-art commercial data race detector, namely Intel R Inspector on 17 applications of various types including 5 servers, 5 client/desktop applications, and 7 scientificones, without utilizingany suppression orannotation mechanisms provided by the product that need users’ input. We examined a total of 1420 false data races and identified two major root causes including address transfer, where one thread passes memory address to another thread. We found more than 62% false data races were caused by address transfer. Based on this observation, we designed and implemented an algorithm that automatically identify address transfer and use the information to prune the false data races. Our evaluation with 8 real-world applications shows that it can effectively prune all false data races caused by unrecognized address transfers, without eliminating any true data race that was originally reported.