GiGAn: Evolutionary mutation testing for C++ object-oriented systems


The current trend in mutation testing is to reduce the great testing effort that it involves, but it should be based on well-studied cost reduction techniques. Evolutionary Mutation Testing (EMT) aims at generating a reduced set of mutants by means of an evolutionary algorithm, which searches for potentially equivalent and difficult to kill mutants to help improve the test suite. However, there is little evidence of its applicability to other contexts beyond WS-BPEL compositions. This study explores its performance when applied to C++ object-oriented programs thanks to a newly developed system, GiGAn. The conducted experiments reveal that EMT shows stable behavior in all the case studies, where the best results are obtained when a low percentage of the mutants is generated. They also support previous studies of EMT when compared to random mutant selection, reinforcing its use for the goal of improving the fault detection capability of the test suite.

Publication DOI:
Divisions: College of Engineering & Physical Sciences
Event Title: 32nd ACM Symposium on Applied Computing
Event Type: Other
Event Location: Marrakesh, Morocco
Event Dates: 2017-04-03 - 2017-04-06
Uncontrolled Keywords: C++,Evolutionary computation,Genetic algorithm,Mutation testing,Object orientation,Software
ISBN: 978-1-450-34486-9
Last Modified: 22 Apr 2024 07:35
Date Deposited: 16 Jan 2017 10:55
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Conference contribution
Published Date: 2017-04-03
Accepted Date: 2016-11-20
Authors: Delgado-Pérez, Pedro
Medina-Bulo, Inmaculada
Segura, Sergio
García-Domínguez, Antonio (ORCID Profile 0000-0002-4744-9150)
Domínguez-Jiménez, Juan José



Version: Accepted Version

License: ["licenses_description_unspecified" not defined]

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