Understanding and detecting real-world performance bugs

Author:

Jin Guoliang1,Song Linhai1,Shi Xiaoming1,Scherpelz Joel1,Lu Shan1

Affiliation:

1. University of Wisconsin-Madison, Madison, WI, USA

Abstract

Developers frequently use inefficient code sequences that could be fixed by simple patches. These inefficient code sequences can cause significant performance degradation and resource waste, referred to as performance bugs. Meager increases in single threaded performance in the multi-core era and increasing emphasis on energy efficiency call for more effort in tackling performance bugs. This paper conducts a comprehensive study of 110 real-world performance bugs that are randomly sampled from five representative software suites (Apache, Chrome, GCC, Mozilla, and MySQL). The findings of this study provide guidance for future work to avoid, expose, detect, and fix performance bugs. Guided by our characteristics study, efficiency rules are extracted from 25 patches and are used to detect performance bugs. 332 previously unknown performance problems are found in the latest versions of MySQL, Apache, and Mozilla applications, including 219 performance problems found by applying rules across applications.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Software

Cited by 187 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Extending the range of bugs that automated program repair can handle;Journal of Systems and Software;2024-03

2. DiagConfig: Configuration Diagnosis of Performance Violations in Configurable Software Systems;Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering;2023-11-30

3. Performance evolution of configurable software systems: an empirical study;Empirical Software Engineering;2023-11

4. BugMiner: Automating Precise Bug Dataset Construction by Code Evolution History Mining;2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE);2023-09-11

5. Early Stopping of Non-productive Performance Testing Experiments Using Measurement Mutations;2023 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA);2023-09-06

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3