PerfRanker: Prioritization of performance regression tests for collection-intensive sotware

Shaikh Mostafa, Xiaoyin Wang, Tao Xie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Regression performance testing is an important but time/resourceconsuming process. Developers need to detect performance regressions as early as possible to reduce their negative impact and fiixing cost. However, conducting regression performance testing frequently (e.g., after each commit) is prohibitively expensive. To address this issue, in this paper, we propose PerfRanker, the first approach to prioritizing test cases in performance regression testing for collection-intensive software, a common type of modern software heavily using collections. Our test prioritization is based on performance impact analysis that estimates the performance impact of a given code revision on a given test execution. The evaluation shows that our approach can cover top 3 test cases whose performance is most afected within top 30% to 37% prioritized test cases, in contrast to top 65% to 79% by three baseline approaches.

Original languageEnglish (US)
Title of host publicationISSTA 2017 - Proceedings of the 26th ACM SIGSOFT International Symposium on Software Testing and Analysis
EditorsKoushik Sen, Tevfik Bultan
PublisherAssociation for Computing Machinery, Inc
Pages23-34
Number of pages12
ISBN (Electronic)9781450350761
DOIs
StatePublished - Jul 10 2017
Event26th ACM SIGSOFT International Symposium on Software Testing and Analysis, ISSTA 2017 - Santa Barbara, United States
Duration: Jul 10 2017Jul 14 2017

Publication series

NameISSTA 2017 - Proceedings of the 26th ACM SIGSOFT International Symposium on Software Testing and Analysis

Other

Other26th ACM SIGSOFT International Symposium on Software Testing and Analysis, ISSTA 2017
CountryUnited States
CitySanta Barbara
Period7/10/177/14/17

Keywords

  • Performance
  • Regression Testing
  • Test Prioritization

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Software

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