An empirical study of JUnit test-suite reduction

Lingming Zhang, Darko Marinov, Lu Zhang, Sarfraz Khurshid

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

Abstract

As test suites grow larger during software evolution, regression testing becomes expensive. To reduce the cost of regression testing, test-suite reduction aims to select a minimal subset of the original test suite that can still satisfy all the test requirements. While traditional test-suite reduction techniques were intensively studied on C programs with specially generated test suites, there are limited studies for test-suite reduction on programs with real-world test suites. In this paper, we investigate test-suite reduction techniques on Java programs with real-world JUnit test suites. We implemented four representative test-suite reduction techniques for JUnit test suites. We performed an empirical study on 19 versions of four real-world Java programs, ranging from 1.89 KLoC to 80.44 KLoC. Our study investigates both the benefits and the costs of test-suite reduction. The results show that the four traditional test-suite reduction techniques can effectively reduce these JUnit test suites without substantially reducing their fault-detection capability. Based on the results, we provide a guideline for achieving cost-effective JUnit test suite reduction.

Original languageEnglish (US)
Title of host publicationProceedings - 22nd IEEE International Symposium on Software Reliability Engineering, ISSRE 2011
Pages170-179
Number of pages10
DOIs
StatePublished - Dec 1 2011
Event22nd IEEE International Symposium on Software Reliability Engineering, ISSRE 2011 - Hiroshima, Japan
Duration: Nov 29 2011Dec 2 2011

Publication series

NameProceedings - International Symposium on Software Reliability Engineering, ISSRE
ISSN (Print)1071-9458

Other

Other22nd IEEE International Symposium on Software Reliability Engineering, ISSRE 2011
CountryJapan
CityHiroshima
Period11/29/1112/2/11

ASJC Scopus subject areas

  • Software
  • Safety, Risk, Reliability and Quality

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