SWORD:一个可扩展的Java程序竞争检测器

2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) Pub Date : 2019-05-25 DOI:10.1109/ICSE-Companion.2019.00042

Yanze Li, Bozhen Liu, Jeff Huang

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引用次数: 10

摘要

我们介绍了SWORD的设计和实现，这是一个可扩展的、完全自动化的Java静态数据竞争检测器，在Eclipse IDE中作为插件实现。SWORD是第一个完整的程序竞争检测器，它可以在几分钟内扩展到数百万行代码，同时在实践中实现良好的精度。SWORD的基础是一种新的算法，它明智地将点分析和事件分析有效地结合在一起，而不会失去精度。我们在大量的大型开源Java项目中对SWORD进行了评估。我们的研究结果表明，与最先进的种族检测器RacerD相比，SWORD检测到更多的种族，报告的假阳性更少。此外，SWORD不需要人工按照RacerD的要求注释代码区域。SWORD还在GUI上显示全面的错误跟踪和比赛配对信息，这使得调试比赛更加容易。演示视频可在https://youtu.be/XQ0CBy7mMaY上获得。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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SWORD: A Scalable Whole Program Race Detector for Java

We present the design and implementation of SWORD, a scalable and fully automated static data race detector for Java, implemented as a plugin in the Eclipse IDE. SWORD is the first whole program race detector that can scale to millions of lines of code in a few minutes while achieving good precision in practice. The cornerstone of SWORD is a new algorithm that judiciously combines points-to analysis and happens-before analysis efficiently, without losing precision. We have evaluated SWORD on an extensive collection of large-scale open source Java projects. Our results show that SWORD detects more races and reports fewer false positives than the state-of-art race detector, RacerD. Moreover, SWORD requires no human effort to annotate code regions as required by RacerD. SWORD also displays comprehensive bug traces and racing pair information on the GUI, which make debugging the races easier. A demo video is available at https://youtu.be/XQ0CBy7mMaY.

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2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)

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