Abstract
Detecting concurrency bugs is becoming increasingly important. Many pattern-based concurrency bug detectors focus on the specific types of interleavings that are correlated to concurrency bugs. To detect multiple types of concurrency bugs, general detectors focus on multiple types of interleaving patterns, including data race pattern, atomicity violation pattern, and atomic-set violation pattern. Unfortunately, they suffer from redundant analysis due to repeated interleavings, which may affect the efficiency of concurrency bug detection. Hence, we propose an approach to identify the repeated interleavings. To the best of our knowledge, this is the first approach that can prune repeated interleavings to improve the efficiency of concurrency bug detection. We apply our approach to existing general detectors (PECAN and Maple) to avoid analyzing repeated interleavings. We evaluated the general detectors with and without our approach, respectively. The experimental results show that the bug detection results are not affected. With our approach, the bug detection time of PECAN and Maple are reduced by 40.0 % and 44.4 %, respectively. Additionally, our approach does not affect the overhead of bug detection, and consumes only a little memory.
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Acknowledgments
This work was partially supported by National High-tech R&D Program of China (863 Program) under Grants 2012AA01A301 and 2012AA010901, by National Science Foundation (NSF) China 61272142, 61103082, 61402492, 61170261 and 61103193, and by Innovation Fund Sponsor Project of Excellent Postgraduate Student B130608.
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Wu, Z., Lu, K., Wang, X. (2015). Identifying Repeated Interleavings to Improve the Efficiency of Concurrency Bug Detection. In: Wang, G., Zomaya, A., Martinez, G., Li, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2015. Lecture Notes in Computer Science(), vol 9531. Springer, Cham. https://doi.org/10.1007/978-3-319-27140-8_13
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DOI: https://doi.org/10.1007/978-3-319-27140-8_13
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