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Authors: Amani Ayad 1 ; Imen Marsit 2 ; JiMeng Loh 1 ; Mohamed Omri 2 and Ali Mili 1

Affiliations: 1 NJIT, Newark NJ and U.S.A. ; 2 MARS Laboratory, University of Sousse and Tunisia

ISBN: 978-989-758-379-7

Keyword(s): Mutation Testing, Software Metrics, Equivalent Mutants, Redundant Mutants, Mutation Score.

Abstract: Mutant generation is the process of generating several variations of a base program by applying elementary modifications to its source code. Mutants are useful only to the extent that they are semantically distinct from the base program; the problem of identifying and weeding out equivalent mutants is an enduring issue in mutation testing. In this paper we take a quantitative approach to this problem where we do not focus on identifying equivalent mutants, but rather on gathering quantitative information about them.

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Paper citation in several formats:
Ayad, A.; Marsit, I.; Loh, J.; Omri, M. and Mili, A. (2019). Quantitative Metrics for Mutation Testing.In Proceedings of the 14th International Conference on Software Technologies - Volume 1: ICSOFT, ISBN 978-989-758-379-7, pages 49-59. DOI: 10.5220/0007841800490059

@conference{icsoft19,
author={Amani Ayad. and Imen Marsit. and JiMeng Loh. and Omri, M. and Ali Mili.},
title={Quantitative Metrics for Mutation Testing},
booktitle={Proceedings of the 14th International Conference on Software Technologies - Volume 1: ICSOFT,},
year={2019},
pages={49-59},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007841800490059},
isbn={978-989-758-379-7},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Software Technologies - Volume 1: ICSOFT,
TI - Quantitative Metrics for Mutation Testing
SN - 978-989-758-379-7
AU - Ayad, A.
AU - Marsit, I.
AU - Loh, J.
AU - Omri, M.
AU - Mili, A.
PY - 2019
SP - 49
EP - 59
DO - 10.5220/0007841800490059

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