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Searching and generating test inputs for mutation testing

Mutation testing is usually regarded as an important method towards fault revealing. Despite this advantage, it has proved to be impractical for industrial use because of its expenses. To this extend, automated techniques are needed in order to apply and reduce the method’s demands. Whilst there is...

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Detalles Bibliográficos
Autores principales: Papadakis, Mike, Malevris, Nicos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing AG 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3629277/
https://www.ncbi.nlm.nih.gov/pubmed/23607084
http://dx.doi.org/10.1186/2193-1801-2-121
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author Papadakis, Mike
Malevris, Nicos
author_facet Papadakis, Mike
Malevris, Nicos
author_sort Papadakis, Mike
collection PubMed
description Mutation testing is usually regarded as an important method towards fault revealing. Despite this advantage, it has proved to be impractical for industrial use because of its expenses. To this extend, automated techniques are needed in order to apply and reduce the method’s demands. Whilst there is much evidence that automated test data generation techniques can effectively automate the testing process, there has been little work on applying them in the context of mutation testing. In this paper, search-based testing is used in order to effectively generate test inputs capable of revealing mutants. To this end, a dynamic execution scheme capable of introducing and guiding the search towards the sought mutants is proposed. Experimentation with the proposed approach reveals its superiority from the previously proposed methods. Additionally, the framework’s feasibility and practicality of producing mutation based test cases are also demonstrated.
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spelling pubmed-36292772013-04-19 Searching and generating test inputs for mutation testing Papadakis, Mike Malevris, Nicos Springerplus Research Mutation testing is usually regarded as an important method towards fault revealing. Despite this advantage, it has proved to be impractical for industrial use because of its expenses. To this extend, automated techniques are needed in order to apply and reduce the method’s demands. Whilst there is much evidence that automated test data generation techniques can effectively automate the testing process, there has been little work on applying them in the context of mutation testing. In this paper, search-based testing is used in order to effectively generate test inputs capable of revealing mutants. To this end, a dynamic execution scheme capable of introducing and guiding the search towards the sought mutants is proposed. Experimentation with the proposed approach reveals its superiority from the previously proposed methods. Additionally, the framework’s feasibility and practicality of producing mutation based test cases are also demonstrated. Springer International Publishing AG 2013-03-21 /pmc/articles/PMC3629277/ /pubmed/23607084 http://dx.doi.org/10.1186/2193-1801-2-121 Text en © Papadakis and Malevris; licensee Springer. 2013 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Papadakis, Mike
Malevris, Nicos
Searching and generating test inputs for mutation testing
title Searching and generating test inputs for mutation testing
title_full Searching and generating test inputs for mutation testing
title_fullStr Searching and generating test inputs for mutation testing
title_full_unstemmed Searching and generating test inputs for mutation testing
title_short Searching and generating test inputs for mutation testing
title_sort searching and generating test inputs for mutation testing
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3629277/
https://www.ncbi.nlm.nih.gov/pubmed/23607084
http://dx.doi.org/10.1186/2193-1801-2-121
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