SHF: Small: Locating and Explaining Faults in Concurrent Software

SHF：小：并发软件中的故障定位和解释

• 批准号: 1116210
• 负责人: Richard Vuduc
• 金额: $ 49.05万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-01 至 2016-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1116210&HistoricalAwards=false
• 关键词: SHF; Small; Locating; Explaining; Faults

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.

从移动的手持设备到高端数据中心服务器，多核和众核处理器在各类计算系统中的迅速采用增加了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非常难以检测和诊断，因为并发行为从根本上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实际负面影响，例如降低开发生产率或并发培训和工具不足，沿着有缺陷软件对最终用户的重大影响。本研究的目的是帮助并发软件的开发人员快速发现和理解缺陷，研究将采用新的方法，结合联合收割机测试和动态分析与自动化的线程交互的事后统计分析。动态分析减少了误报故障报告，统计数据分析利用并发执行的固有非确定性来产生候选故障的信息优先级排序。由此产生的技术将大大提高调试的生产力，帮助开发人员磨练在最有可能的原因程序，由此产生的技术和工具将是变革性的，并将自动故障定位并发软件。研究结果将对并发软件实践、研究和教育产生更广泛的影响。这项研究将为具有全球竞争力的学生在并发软件和并行思维的新兴领域做好准备，沿着的是为软件工程和计算科学与工程的学生提供智力桥梁，并推进多样性目标。此外，成功地改进并发软件的故障定位技术将导致软件质量的提高，从而使依赖软件的社会各阶层受益。