SHF: Small: Locating and Explaining Faults in Concurrent Software

多核和多核处理器在每一类计算系统中的快速采用-从移动手持设备到高端数据中心服务器-正在增加我们对并发软件的依赖。然而，并发程序中的缺陷对于开发人员来说是出了名的难以检测和诊断，因为从根本上讲，并发行为比顺序行为更难推理。主要软件供应商报告了并发故障对软件开发的切实负面影响，例如开发生产率降低或并发培训和工具不足，以及有缺陷的软件对最终用户的重大影响。该研究项目的目标是帮助并发软件开发人员快速发现和了解缺陷。研究将采用新的方法，将测试和动态分析与线程交互的自动事后统计分析相结合。动态分析减少了误报故障报告，而统计数据分析利用了并发执行固有的不确定性来产生候选故障的信息优先排序。所产生的技术将通过帮助开发人员磨练最可能的编程原因来极大地提高调试效率。所产生的技术和工具将是变革性的，并将自动化并发软件的故障定位。研究结果将对并发软件实践、研究和教育的最新水平产生更广泛的影响。这项研究将培养在并行软件和并行思维这一新兴领域具有全球竞争力的学生，并在软件工程和计算科学与工程学生之间建立智力桥梁，并推进多样性目标。此外，在改进并发软件的故障定位技术方面的成功将导致软件质量的提高，从而使依赖软件的所有社会部门受益。

The rapid adoption of multicore and manycore processors in every class of computing systems---from mobile handheld devices to high-end data center servers---is increasing our dependence on concurrent software. However, defects in concurrent programs are notoriously difficult for developers to detect and diagnose, because concurrent behavior is fundamentally harder to reason about than sequential behavior. Major software vendors report the tangible negative impacts on software development from concurrent faults, such as reduced development productivity or inadequate concurrency training and tools, along with the significant impact on end-users from defective software. The goal of this research project is to help developers of concurrent software find and understand defects quickly.The research will employ novel approaches that combine testing and dynamic analysis with automated post-mortem statistical analysis of thread interactions. Dynamic analysis reduces false positive fault reports, and statistical data analysis exploits the inherent non-determinism of concurrent execution to produce informative prioritized rankings of candidate faults. The resulting techniques will greatly improve debugging productivity by helping the developer to hone in on the most likely causes of program the resulting techniques and tools will be transformative, and will automate fault-localization for concurrent software. The results of the research will have broader impacts on the state-of-the-art in concurrent software practice, research, and education. The research will prepare globally competitive students in the emerging area of concurrent software and parallel thinking, along with providing intellectual bridges between students in software engineering and in computational science and engineering, and advance diversity goals. Additionally, successes in improving fault-localization techniques for concurrent software will lead to improvements in software quality and, thus, benefit all segments of society that depend on software.