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Harmful data races hidden in concurrent programs are hard to be detected due to non-determinism. Many race detectors report a large number of benign data races. To detect the harmful data races automatically, previous tools dynamically execute program and actively insert delay to create real race condition, checking whether failure occurs due to the race. If so, a harmful race is detected. However,...
Data races hidden in concurrent programs have caused severe failures. To improve the reliability, many race detectors are proposed. However, most of the reported races are not harmful, which consumes manual effort to identify the harmful races. This paper proposes Race Checker that can detect the potential races and identify the harmful races effectively and efficiently. Unlike previous detectors,...
Data races widely exist in concurrent programs and the harmful races have caused severe failures. To detect the harmful races, previous tools verify all the races, identifying the harmful ones. However, efficiency is affected when there are a large number of races needed to be verified. The multicore technology trend worsens this problem. Unlike previous work, to detect the harmful races, we try to...
Races hidden in concurrent programs can lead to harmful bugs. These bugs are difficult to detect due to their non-deterministic characteristics. Previous work has tried to dynamically verify races in actual executions to check whether they would lead to failures. However, it is inefficient to verify all the races to find the harmful bugs if there are a large number of races. To improve the efficiency,...
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