Dynamic generation of test cases with metaheuristics

Autores
Lanzarini, Laura Cristina; Battaiotto, Pedro Eduardo
Año de publicación
2010
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The resolution of optimization problems is of great interest nowadays and has encouraged the development of various information technology methods to attempt solving them. There are several problems related to Software Engineering that can be solved by using this approach. In this paper, a new alternative based on the combination of population metaheuristics with a Tabu List to solve the problem of test cases generation when testing software is presented. This problem is of great importance for the development of software with a high computational cost and which is generally hard to solve. The performance of the solution proposed has been tested on a set of varying complexity programs. The results obtained show that the method proposed allows obtaining a reduced test data set in a suitable timeframe and with a greater coverage than conventional methods such as Random Method or Tabu Search.
Facultad de Informática
Materia
Ciencias Informáticas
Heuristic methods
Testing tools (e.g., data generators, coverage testing)
Algorithms
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/9675

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spelling Dynamic generation of test cases with metaheuristicsLanzarini, Laura CristinaBattaiotto, Pedro EduardoCiencias InformáticasHeuristic methodsTesting tools (e.g., data generators, coverage testing)AlgorithmsThe resolution of optimization problems is of great interest nowadays and has encouraged the development of various information technology methods to attempt solving them. There are several problems related to Software Engineering that can be solved by using this approach. In this paper, a new alternative based on the combination of population metaheuristics with a Tabu List to solve the problem of test cases generation when testing software is presented. This problem is of great importance for the development of software with a high computational cost and which is generally hard to solve. The performance of the solution proposed has been tested on a set of varying complexity programs. The results obtained show that the method proposed allows obtaining a reduced test data set in a suitable timeframe and with a greater coverage than conventional methods such as Random Method or Tabu Search.Facultad de Informática2010-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf91-96http://sedici.unlp.edu.ar/handle/10915/9675enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Jun10-8.pdfinfo:eu-repo/semantics/altIdentifier/issn/1666-6038info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc/3.0/Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:50:45Zoai:sedici.unlp.edu.ar:10915/9675Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:50:45.281SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Dynamic generation of test cases with metaheuristics
title Dynamic generation of test cases with metaheuristics
spellingShingle Dynamic generation of test cases with metaheuristics
Lanzarini, Laura Cristina
Ciencias Informáticas
Heuristic methods
Testing tools (e.g., data generators, coverage testing)
Algorithms
title_short Dynamic generation of test cases with metaheuristics
title_full Dynamic generation of test cases with metaheuristics
title_fullStr Dynamic generation of test cases with metaheuristics
title_full_unstemmed Dynamic generation of test cases with metaheuristics
title_sort Dynamic generation of test cases with metaheuristics
dc.creator.none.fl_str_mv Lanzarini, Laura Cristina
Battaiotto, Pedro Eduardo
author Lanzarini, Laura Cristina
author_facet Lanzarini, Laura Cristina
Battaiotto, Pedro Eduardo
author_role author
author2 Battaiotto, Pedro Eduardo
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Heuristic methods
Testing tools (e.g., data generators, coverage testing)
Algorithms
topic Ciencias Informáticas
Heuristic methods
Testing tools (e.g., data generators, coverage testing)
Algorithms
dc.description.none.fl_txt_mv The resolution of optimization problems is of great interest nowadays and has encouraged the development of various information technology methods to attempt solving them. There are several problems related to Software Engineering that can be solved by using this approach. In this paper, a new alternative based on the combination of population metaheuristics with a Tabu List to solve the problem of test cases generation when testing software is presented. This problem is of great importance for the development of software with a high computational cost and which is generally hard to solve. The performance of the solution proposed has been tested on a set of varying complexity programs. The results obtained show that the method proposed allows obtaining a reduced test data set in a suitable timeframe and with a greater coverage than conventional methods such as Random Method or Tabu Search.
Facultad de Informática
description The resolution of optimization problems is of great interest nowadays and has encouraged the development of various information technology methods to attempt solving them. There are several problems related to Software Engineering that can be solved by using this approach. In this paper, a new alternative based on the combination of population metaheuristics with a Tabu List to solve the problem of test cases generation when testing software is presented. This problem is of great importance for the development of software with a high computational cost and which is generally hard to solve. The performance of the solution proposed has been tested on a set of varying complexity programs. The results obtained show that the method proposed allows obtaining a reduced test data set in a suitable timeframe and with a greater coverage than conventional methods such as Random Method or Tabu Search.
publishDate 2010
dc.date.none.fl_str_mv 2010-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
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info:eu-repo/semantics/altIdentifier/issn/1666-6038
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
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instname:Universidad Nacional de La Plata
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collection SEDICI (UNLP)
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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