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Authors: Imen Marsit 1 ; Mohamed Nazih Omri 1 and Ali Mili 2

Affiliations: 1 University of Sousse, Tunisia ; 2 New Jersey Institute of Technology, United States

ISBN: 978-989-758-262-2

ISSN: 2184-2833

Keyword(s): Mutation Testing, Mutant Survival Rate, Semantic Metrics.

Related Ontology Subjects/Areas/Topics: Software Engineering ; Software Engineering Methods and Techniques ; Software Metrics ; Software Project Management ; Software Testing and Maintenance

Abstract: Mutation testing is often used to assess the quality of a test suite by analyzing its ability to distinguish between a base program and its mutants. The main threat to the validity/ reliability of this assessment approach is that many mutants may be syntactically distinct from the base, yet functionally equivalent to it. The problem of identifying equivalent mutants and excluding them from consideration is the focus of much recent research. In this paper we argue that it is not necessary to identify individual equivalent mutants and count them; rather it is sufficient to estimate their number. To do so, we consider the question: what makes a program prone to produce equivalent mutants? Our answer is: redundancy does. Consequently, we introduce a number of program metrics that capture various dimensions of redundancy in a program, and show empirically that they are statistically linked to the rate of equivalent mutants.

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Paper citation in several formats:
Marsit, I.; Omri, M. and Mili, A. (2017). Estimating the Survival Rate of Mutants.In Proceedings of the 12th International Conference on Software Technologies - Volume 1: ICSOFT, ISBN 978-989-758-262-2, ISSN 2184-2833, pages 208-213. DOI: 10.5220/0006392802080213

author={Imen Marsit. and Omri, M. and Ali Mili.},
title={Estimating the Survival Rate of Mutants},
booktitle={Proceedings of the 12th International Conference on Software Technologies - Volume 1: ICSOFT,},


JO - Proceedings of the 12th International Conference on Software Technologies - Volume 1: ICSOFT,
TI - Estimating the Survival Rate of Mutants
SN - 978-989-758-262-2
AU - Marsit, I.
AU - Omri, M.
AU - Mili, A.
PY - 2017
SP - 208
EP - 213
DO - 10.5220/0006392802080213

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