An Automated Technique for Analysis of Orthogonal Variability Models based on Anti-patterns Detection using DL reasoning

Autores
Oyarzun, Ángela; Braun, Germán; Cecchi, Laura; Fillottrani, Pablo Rubén
Año de publicación
2019
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
During a Software Product Line (SPL) variability management, model validation is crucial so as to detect faults in early development stages and avoid affecting derived products quality. Therefore, the automated variability analysis has emerged for translating and validating variability models. In this work, we present a catalogue of anti-patterns, which describes scenarios associated to the detection of problems in a SPL. Moreover, we extend crowd-variability, a novel graphical tool designed for modelling and validating Orthogonal Variability Models (OVM), for detecting such anti-patterns using Description Logics (DL)-based reasoning services.
XI Workshop Innovación en Sistemas de Software.
Red de Universidades con Carreras en Informática
Materia
Ciencias Informáticas
Software product lines
Orthogonal Variability Models
Description logics
Graphical tools for modelling variability
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/91150

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oai_identifier_str oai:sedici.unlp.edu.ar:10915/91150
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network_name_str SEDICI (UNLP)
spelling An Automated Technique for Analysis of Orthogonal Variability Models based on Anti-patterns Detection using DL reasoningOyarzun, ÁngelaBraun, GermánCecchi, LauraFillottrani, Pablo RubénCiencias InformáticasSoftware product linesOrthogonal Variability ModelsDescription logicsGraphical tools for modelling variabilityDuring a Software Product Line (SPL) variability management, model validation is crucial so as to detect faults in early development stages and avoid affecting derived products quality. Therefore, the automated variability analysis has emerged for translating and validating variability models. In this work, we present a catalogue of anti-patterns, which describes scenarios associated to the detection of problems in a SPL. Moreover, we extend crowd-variability, a novel graphical tool designed for modelling and validating Orthogonal Variability Models (OVM), for detecting such anti-patterns using Description Logics (DL)-based reasoning services.XI Workshop Innovación en Sistemas de Software.Red de Universidades con Carreras en Informática2019-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf940-949http://sedici.unlp.edu.ar/handle/10915/91150enginfo:eu-repo/semantics/altIdentifier/isbn/978-987-688-377-1info:eu-repo/semantics/reference/hdl/10915/90359info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:19:03Zoai:sedici.unlp.edu.ar:10915/91150Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:19:03.576SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv An Automated Technique for Analysis of Orthogonal Variability Models based on Anti-patterns Detection using DL reasoning
title An Automated Technique for Analysis of Orthogonal Variability Models based on Anti-patterns Detection using DL reasoning
spellingShingle An Automated Technique for Analysis of Orthogonal Variability Models based on Anti-patterns Detection using DL reasoning
Oyarzun, Ángela
Ciencias Informáticas
Software product lines
Orthogonal Variability Models
Description logics
Graphical tools for modelling variability
title_short An Automated Technique for Analysis of Orthogonal Variability Models based on Anti-patterns Detection using DL reasoning
title_full An Automated Technique for Analysis of Orthogonal Variability Models based on Anti-patterns Detection using DL reasoning
title_fullStr An Automated Technique for Analysis of Orthogonal Variability Models based on Anti-patterns Detection using DL reasoning
title_full_unstemmed An Automated Technique for Analysis of Orthogonal Variability Models based on Anti-patterns Detection using DL reasoning
title_sort An Automated Technique for Analysis of Orthogonal Variability Models based on Anti-patterns Detection using DL reasoning
dc.creator.none.fl_str_mv Oyarzun, Ángela
Braun, Germán
Cecchi, Laura
Fillottrani, Pablo Rubén
author Oyarzun, Ángela
author_facet Oyarzun, Ángela
Braun, Germán
Cecchi, Laura
Fillottrani, Pablo Rubén
author_role author
author2 Braun, Germán
Cecchi, Laura
Fillottrani, Pablo Rubén
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Software product lines
Orthogonal Variability Models
Description logics
Graphical tools for modelling variability
topic Ciencias Informáticas
Software product lines
Orthogonal Variability Models
Description logics
Graphical tools for modelling variability
dc.description.none.fl_txt_mv During a Software Product Line (SPL) variability management, model validation is crucial so as to detect faults in early development stages and avoid affecting derived products quality. Therefore, the automated variability analysis has emerged for translating and validating variability models. In this work, we present a catalogue of anti-patterns, which describes scenarios associated to the detection of problems in a SPL. Moreover, we extend crowd-variability, a novel graphical tool designed for modelling and validating Orthogonal Variability Models (OVM), for detecting such anti-patterns using Description Logics (DL)-based reasoning services.
XI Workshop Innovación en Sistemas de Software.
Red de Universidades con Carreras en Informática
description During a Software Product Line (SPL) variability management, model validation is crucial so as to detect faults in early development stages and avoid affecting derived products quality. Therefore, the automated variability analysis has emerged for translating and validating variability models. In this work, we present a catalogue of anti-patterns, which describes scenarios associated to the detection of problems in a SPL. Moreover, we extend crowd-variability, a novel graphical tool designed for modelling and validating Orthogonal Variability Models (OVM), for detecting such anti-patterns using Description Logics (DL)-based reasoning services.
publishDate 2019
dc.date.none.fl_str_mv 2019-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
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status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/91150
url http://sedici.unlp.edu.ar/handle/10915/91150
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-987-688-377-1
info:eu-repo/semantics/reference/hdl/10915/90359
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
940-949
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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