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DigHR: precise dynamic detection of hidden races with weak causal relation analysis

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Abstract

Present advanced precise race detection techniques leverage strict causal relation to locate data races, leading to false negatives and missing many hidden races. In this paper, we present a novel race detection technique, called DigHR, which can detect more hidden races than existing precise techniques. DigHR is based on a weak causal relation, called afterward-confirm (AC) relation, which relaxes restrictions of existing causal relations and is proved to be sound. To represent AC relations between events, we propose a new data structure, called water-flow graph, which enable DigHR to analyze AC relations and detect hidden races at run-time. We have implemented DigHR in C/C++ and evaluated the effectiveness of DigHR by detecting races from real-world benchmarks and applications. The experimental results show that DigHR can precisely detect 21% more races than previous techniques, including FastTrack and CP.

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Notes

  1. The source code of DigHR is available at https://github.com/pluohust/DigHR.

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Acknowledgements

This work is supported by National Science Foundation of China under Grant No. 61672249 and National 973 Fundamental Basic Research Program under Grant No. 2014CB340600.

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Authors and Affiliations

  1. Cluster and Grid Computing Lab, Services Computing Technology and System Lab, Huazhong University of Science and Technology, Wuhan, China

    Peng Luo, Deqing Zou, Hai Jin, Yajuan Du, Long Zheng & Jinan Shen

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  1. Peng Luo
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  2. Deqing Zou
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  3. Hai Jin
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Correspondence to Deqing Zou.

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Luo, P., Zou, D., Jin, H. et al. DigHR: precise dynamic detection of hidden races with weak causal relation analysis. J Supercomput 74, 2684–2704 (2018). https://doi.org/10.1007/s11227-018-2307-8

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