Test suite reduction with selective redundancy

Jeffrey, Dennis; Gupta, Neelam

doi:10.1109/icsm.2005.88

Cited by 86 publications

(70 citation statements)

References 15 publications

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“…In this study, we use two dependent variables commonly used by traditional test-suite reduction studies [4], [14], [17] [23]. We chose SIR because it is very widely used.…”

Section: Dependent Variables and Metricsmentioning

confidence: 99%

“…There is additional work aiming to improve the fault-detection capability of reduced test suites. For example, Jeffrey et al [17], [30] modified the heuristic algorithm proposed by Harrold et al [2] by selecting redundant test cases to maintain the fault-detection capability.…”

Section: Related Workmentioning

confidence: 99%

“…(1) The subject programs in our study are larger than those used in previous studies; our programs are in Java not in C as in most existing reearch [2], [4], [9], [15], [17], and coding styles in Java and C can differ. (2) The nature of tests is substantially different: we focus on tests for small units of code from a larger system and hence some tests may have mutually disjoint execution paths, whereas previous studies looked at small programs where many tests execute the same main method albeit on different inputs.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Empirical Study of JUnit Test-Suite Reduction

Zhang

Marinov

et al. 2011

2011 IEEE 22nd International Symposium on Software Reliability Engineering

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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 testsuite reduction.

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“…In this study, we use two dependent variables commonly used by traditional test-suite reduction studies [4], [14], [17] [23]. We chose SIR because it is very widely used.…”

Section: Dependent Variables and Metricsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Empirical Study of JUnit Test-Suite Reduction

Zhang

Marinov

et al. 2011

2011 IEEE 22nd International Symposium on Software Reliability Engineering

View full text Add to dashboard Cite

show abstract

“…• With Jeffrey [20], Gupta adds "selective redundancy" to the algorithm. "Selective redundancy" makes it possible to select test cases that, for any given test requirement, provide the same coverage as another previously selected test case, but that adds the coverage of a new, different test requirement.…”

Section: Fig 3 the Optimal Test Suite Reduction Problemmentioning

confidence: 99%

“…In their paper [20], Jeffrey and Gupta show, using the same title that leads this section, a small program to exemplify their algorithm with selective redundancy, which has been translated into the Java program shown in Figure 7. For this class, MuJava generates 48 traditional (15 of them are functionally-equivalent) and 6 class mutants for this program.…”

Section: "A Motivational Example"mentioning

confidence: 99%