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Authors: Zhiyi Zhang 1 ; Dongjiang You 1 ; Zhenyu Chen 1 ; Yuming Zhou 2 and Baowen Xu 2

Affiliations: 1 Nanjing University, Software Institute and Nanjing University, China ; 2 Nanjing University, China

ISBN: 978-989-8425-58-4

Keyword(s): Mutation Selection; Mutation Testing; Mutation Analysis

Abstract: In previous research, many mutation selection techniques have been proposed to reduce the cost of mutation analysis. After a mutant subset is selected, researchers could obtain a test suite which can detect all mutants in the mutant subset. Then they run all mutants over this test suite, and the detection ratio to all mutants is used to evaluate the effectiveness of mutation selection techniques. The higher the ratio is, the better this selection technique is. Obviously, this measurement has a presumption that the set of all mutants is the best to evaluate test cases. However, there is no clearly evidence to support this presumption. So we conducted an experiment to answer the question whether the set of all mutants is the best to evaluate test cases. In this paper, our experiment results show that a subset of mutants may be more similar to faults than all the mutants. Two evaluation metrics were used to measure the similarity – rank and distance. This finding reveals that it may be m ore appropriate to use a subset rather than all the mutants at hand to evaluate the fault detection capability of test cases. (More)

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Paper citation in several formats:
Zhang, Z.; You, D.; Chen, Z.; Zhou, Y. and Xu, B. (2011). Mutation Selection: Some Could be Better than All.In Proceeding of the 1st International Workshop on Evidential Assessment of Software Technologies - Volume 1: EAST, (ENASE 2011) ISBN 978-989-8425-58-4, pages 10-17

@conference{east11,
author={Zhiyi Zhang. and Dongjiang You. and Zhenyu Chen. and Yuming Zhou. and Baowen Xu.},
title={Mutation Selection: Some Could be Better than All},
booktitle={Proceeding of the 1st International Workshop on Evidential Assessment of Software Technologies - Volume 1: EAST, (ENASE 2011)},
year={2011},
pages={10-17},
publisher={SciTePress},
organization={INSTICC},
doi={},
isbn={978-989-8425-58-4},
}

TY - CONF

JO - Proceeding of the 1st International Workshop on Evidential Assessment of Software Technologies - Volume 1: EAST, (ENASE 2011)
TI - Mutation Selection: Some Could be Better than All
SN - 978-989-8425-58-4
AU - Zhang, Z.
AU - You, D.
AU - Chen, Z.
AU - Zhou, Y.
AU - Xu, B.
PY - 2011
SP - 10
EP - 17
DO -

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