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。 性能错误是减慢执行速度的编程错误。 最近已经提出了许多技术来检测各种性能错误。 然而，仍然存在许多现有技术无法检测到的性能缺陷。 此外，性能缺陷的关键和实际方面尚未得到应有的重视：开发人员修复检测到的性能缺陷的可能性有多大？为了显着提高软件性能，该项目将开发一套新技术，重点关注一类非常严重的性能缺陷。开发人员可能会修复这些问题，特别是具有非侵入式修复的性能错误。 具有非侵入性修复的性能错误很可能被开发人员修复，因为修复的好处（即代码加速）显然超过了修复的缺点（例如，引入新的正确性错误、破坏良好的软件工程实践、开发时间和精力、 ETC）。 该项目将解决三个基本挑战：(1) 哪些性能错误具有非侵入式修复以及它们的定义特征是什么？ (2) 如何自动检测性能错误以及如何确定其修复是非侵入性的？ (3)如何自动修复一些检测到的性能bug？ 这项工作将拓宽我们对软件性能的一个尚未充分研究但很重要的方面的理解，并将提供自动化解决方案来提高软件性能。