CAREER: Combating Performance Bugs in Software Systems

职业：对抗软件系统中的性能错误

• 批准号: 1514189
• 负责人: Shan Lu
• 金额: $ 23.89万
• 依托单位: University of Chicago
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2017-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1514189&HistoricalAwards=false
• 关键词: CAREER; Combating; Performance; Bugs; Software

Performance bugs cause unintended performance degradation and energy waste in mainstream software. These bugs can easily slow down production software for several times and are posing increasing threat to software quality with the meager increases in single threaded performance in multi-core era and an increasing emphasis on energy efficiency.Previous works for performance bugs, including testing and profiling, mostly treat software as a black-box, and are usually too late or ineffective in preventing the damage of performance bugs. This NSF CAREER research project seeks to develop systems and tools that take a white-box approach to addressing the open problem of performance bugs. First, it conducts an empirical study to enrich the understanding of performance bugs in real-world. Second, it develops tools that can automatically detect performance bugs before, during, and after bug manifestation. Third, it designs a testing framework to expose performance bugs before software release. Finally, it also looks at the performance bug issue in multi-threaded programs.The education focus of this project is to broaden the software curriculum to bring students more awareness and exercise of performance and correctness issues in software, especially multi-threaded software.This research will improve the understanding of performance waste problem in software, provide substantial tool support to help lower software development and performance testing costs, and improve software users' everyday experience through faster software. It will also help improve the energy efficiency of production-run software and protect environment in the field.

性能错误导致主流软件中的意外性能降解和能源浪费。这些错误很容易减慢生产软件的速度几次，并随着多核时代的单线螺纹性能的微薄提高以及对能源效率的越来越多的质量提高，对软件质量构成了威胁，并且对性能错误进行了自我提高的作品，包括测试和分析，主要是将软件视为黑色盒子，并且通常在防止表现错误的损害中造成较晚或无效。 NSF职业研究项目旨在开发系统和工具，以采用白色框方法来解决绩效错误的开放问题。首先，它进行了一项实证研究，以丰富对现实世界中绩效错误的理解。其次，它开发了可以在错误表现前，期间和之后自动检测性能错误的工具。第三，它设计了一个测试框架，以在软件发布之前暴露性能错误。最后，它还研究了多线程程序中的性能问题问题。该项目的教育重点是扩大软件课程，以使学生更加认识，对软件中的性能和正确性问题，尤其是多线程软件。这项研究将改善对软件中性能浪费问题的理解，并提供软件开发的大量工具，以帮助软件开发和降低软件用户的软件使用软件的经验，并通过FASSS来改善软件的绩效测试成本，并通过Faster来改善软件的经验。它还将有助于提高生产运行软件的能源效率并保护该领域的环境。