SHF: Small: RUI: Characterizing, Detecting, and Fixing Performance Bugs That Have Non-Intrusive Fixes

SHF：小：RUI：表征、检测和修复具有非侵入式修复的性能错误

• 批准号: 1528134
• 负责人: Adrian Nistor
• 金额: $ 24.14万
• 依托单位: Chapman University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-01 至 2016-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1528134&HistoricalAwards=false
• 关键词: SHF; Small; RUI; Characterizing; Detecting

Software performance is critical for the success of a softwareproject. Performance bugs are programming errors that slow downexecution. Many recent techniques have been proposed to detectvarious performance bugs. However, there are still many performancebugs that cannot be detected by existing techniques. Furthermore, acrucial and practical aspect of performance bugs has not received theattention it deserves: How likely are developers to fix a detectedperformance bug?To significantly improve software performance, this project willdevelop a set of novel techniques that focus on a class of performancebugs that are very likely to be fixed by developers, specifically onperformance bugs that have non-intrusive fixes. Performance bugs thathave non-intrusive fixes are very likely to be fixed by developersbecause the benefits of the fix (i.e., code speedup) clearly outweighthe drawbacks of the fix (e.g., introducing new correctness bugs,breaking good software engineering practices, development time andeffort, etc). This project will address three fundamental challenges:(1) What performance bugs have non-intrusive fixes and what are theirdefining characteristics? (2) How to automatically detect performancebugs and how to establish that their fixes will be non-intrusive? (3)How to automatically fix some of the detected performance bugs? Thiswork will broaden our understanding of an understudied yet importantaspect of software performance and will provide automated solutions toimprove software performance.

软件性能对于软件项目的成功至关重要。 性能错误是缓慢执行的编程错误。 已经提出了许多最近的技术来检测性能错误。 但是，仍然有许多性能吸烟无法通过现有技术检测到。 此外，性能错误的实质性和实用方面尚未收到应有的：修复检测到的性能错误的可能性有多大的可能性？显着提高软件性能，该项目将开发一系列新型技术，这些技术将专注于一类性能很多新技术，而这些绩效次数很可能是由开发人员修复的，特别是在开发人员上，特别是在不断增加的funsement bugs上，具有非吸引力的修复。 开发人员很可能会确定不侵入性修复程序的性能错误，因为修复程序的好处（即代码速度）显然超过了修复程序的缺点（例如，引入新的正确性错误，打破了良好的软件工程实践，开发时间和富裕等）。 该项目将解决三个基本挑战：（1）哪些性能错误具有非侵入性修复程序，其定义特征是什么？ （2）如何自动检测性能次数以及如何确定其修复程序将是无侵入性的？ （3）如何自动修复一些检测到的性能错误？ 这项工作将扩大我们对软件性能的经过研究的但重要的知识的理解，并将提供自动化的解决方案，以促进软件性能。