Quantitative Metrics for Mutation Testing

Amani Ayad, Imen Marsit, JiMeng Loh, Mohamed Omri, Ali Mili

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 Harvard Style

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


in Bibtex Style

@conference{icsoft19,
author={Amani Ayad and Imen Marsit and JiMeng Loh and Mohamed Omri 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},
}


in EndNote Style

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