An Approach Based on Feature Models and Quality Criteria for Adapting Component-Based Systems

Autores
Sánchez, Luis Emiliano; Diaz Pace, Jorge Andres; Zunino Suarez, Alejandro Octavio; Moisan, Sabine; Rigault, Jean-Paul
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Background: Feature modeling has been widely used in domain engineering for thedevelopment and configuration of software product lines. A feature model represents the set of possible products or configurations to apply in a given context. Recently, this formalism has been applied to the runtime (re-)configuration of systems with high variability and running in changing contexts. These systems must adapt by updating their component assembly configuration at runtime, while minimizing the impact of such changes on the quality of service. For this reason the selection of a good system configuration is seen as an optimization problem based on quality attribute criteria.Methods:We propose an approach for system adaptation based on the specification,measurement and optimization of quality attribute properties on feature models.Furthermore, we describe its integration into a platform for supporting theself-adaptation of component-based systems. Feature models are annotated withquality attribute properties and metrics, and then an efficient algorithm is used to deal with the optimization problem.Results and conclusions:Two performance properties -- frame processing time andreconfiguration time -- are estimated with our model against measurements obtainedfrom the running system to show the accuracy of metrics on feature models forestimating quality attribute properties. The results show evidence that these metrics are reasonably accurate for measuring performance properties on a realistic component-based computer vision system.
Fil: Sánchez, Luis Emiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Diaz Pace, Jorge Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Zunino Suarez, Alejandro Octavio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Moisan, Sabine. Institut National de Recherche en Informatique et en Automatique; Francia
Fil: Rigault, Jean-Paul. Institut National de Recherche en Informatique et en Automatique; Francia
Materia
FEATURE MODELS
RUNTIME ADAPTATION
QUALITY ATTRIBUTES
OPTIMIZATION
COMPONENT-BASED SOFTWARE ENGINEERING
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/58096
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling An Approach Based on Feature Models and Quality Criteria for Adapting Component-Based SystemsSánchez, Luis EmilianoDiaz Pace, Jorge AndresZunino Suarez, Alejandro OctavioMoisan, SabineRigault, Jean-PaulFEATURE MODELSRUNTIME ADAPTATIONQUALITY ATTRIBUTESOPTIMIZATIONCOMPONENT-BASED SOFTWARE ENGINEERINGhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Background: Feature modeling has been widely used in domain engineering for thedevelopment and configuration of software product lines. A feature model represents the set of possible products or configurations to apply in a given context. Recently, this formalism has been applied to the runtime (re-)configuration of systems with high variability and running in changing contexts. These systems must adapt by updating their component assembly configuration at runtime, while minimizing the impact of such changes on the quality of service. For this reason the selection of a good system configuration is seen as an optimization problem based on quality attribute criteria.Methods:We propose an approach for system adaptation based on the specification,measurement and optimization of quality attribute properties on feature models.Furthermore, we describe its integration into a platform for supporting theself-adaptation of component-based systems. Feature models are annotated withquality attribute properties and metrics, and then an efficient algorithm is used to deal with the optimization problem.Results and conclusions:Two performance properties -- frame processing time andreconfiguration time -- are estimated with our model against measurements obtainedfrom the running system to show the accuracy of metrics on feature models forestimating quality attribute properties. The results show evidence that these metrics are reasonably accurate for measuring performance properties on a realistic component-based computer vision system.Fil: Sánchez, Luis Emiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaFil: Diaz Pace, Jorge Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaFil: Zunino Suarez, Alejandro Octavio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaFil: Moisan, Sabine. Institut National de Recherche en Informatique et en Automatique; FranciaFil: Rigault, Jean-Paul. Institut National de Recherche en Informatique et en Automatique; FranciaSpringer2015-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/58096Sánchez, Luis Emiliano; Diaz Pace, Jorge Andres; Zunino Suarez, Alejandro Octavio; Moisan, Sabine; Rigault, Jean-Paul; An Approach Based on Feature Models and Quality Criteria for Adapting Component-Based Systems; Springer; Journal of Software Engineering Research and Development; 3; 10; 6-2015; 1-302195-1721CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1186/s40411-015-0022-1info:eu-repo/semantics/altIdentifier/doi/10.1186/s40411-015-0022-1info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:44:00Zoai:ri.conicet.gov.ar:11336/58096instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:44:01.219CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv An Approach Based on Feature Models and Quality Criteria for Adapting Component-Based Systems
title An Approach Based on Feature Models and Quality Criteria for Adapting Component-Based Systems
spellingShingle An Approach Based on Feature Models and Quality Criteria for Adapting Component-Based Systems
Sánchez, Luis Emiliano
FEATURE MODELS
RUNTIME ADAPTATION
QUALITY ATTRIBUTES
OPTIMIZATION
COMPONENT-BASED SOFTWARE ENGINEERING
title_short An Approach Based on Feature Models and Quality Criteria for Adapting Component-Based Systems
title_full An Approach Based on Feature Models and Quality Criteria for Adapting Component-Based Systems
title_fullStr An Approach Based on Feature Models and Quality Criteria for Adapting Component-Based Systems
title_full_unstemmed An Approach Based on Feature Models and Quality Criteria for Adapting Component-Based Systems
title_sort An Approach Based on Feature Models and Quality Criteria for Adapting Component-Based Systems
dc.creator.none.fl_str_mv Sánchez, Luis Emiliano
Diaz Pace, Jorge Andres
Zunino Suarez, Alejandro Octavio
Moisan, Sabine
Rigault, Jean-Paul
author Sánchez, Luis Emiliano
author_facet Sánchez, Luis Emiliano
Diaz Pace, Jorge Andres
Zunino Suarez, Alejandro Octavio
Moisan, Sabine
Rigault, Jean-Paul
author_role author
author2 Diaz Pace, Jorge Andres
Zunino Suarez, Alejandro Octavio
Moisan, Sabine
Rigault, Jean-Paul
author2_role author
author
author
author
dc.subject.none.fl_str_mv FEATURE MODELS
RUNTIME ADAPTATION
QUALITY ATTRIBUTES
OPTIMIZATION
COMPONENT-BASED SOFTWARE ENGINEERING
topic FEATURE MODELS
RUNTIME ADAPTATION
QUALITY ATTRIBUTES
OPTIMIZATION
COMPONENT-BASED SOFTWARE ENGINEERING
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Background: Feature modeling has been widely used in domain engineering for thedevelopment and configuration of software product lines. A feature model represents the set of possible products or configurations to apply in a given context. Recently, this formalism has been applied to the runtime (re-)configuration of systems with high variability and running in changing contexts. These systems must adapt by updating their component assembly configuration at runtime, while minimizing the impact of such changes on the quality of service. For this reason the selection of a good system configuration is seen as an optimization problem based on quality attribute criteria.Methods:We propose an approach for system adaptation based on the specification,measurement and optimization of quality attribute properties on feature models.Furthermore, we describe its integration into a platform for supporting theself-adaptation of component-based systems. Feature models are annotated withquality attribute properties and metrics, and then an efficient algorithm is used to deal with the optimization problem.Results and conclusions:Two performance properties -- frame processing time andreconfiguration time -- are estimated with our model against measurements obtainedfrom the running system to show the accuracy of metrics on feature models forestimating quality attribute properties. The results show evidence that these metrics are reasonably accurate for measuring performance properties on a realistic component-based computer vision system.
Fil: Sánchez, Luis Emiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Diaz Pace, Jorge Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Zunino Suarez, Alejandro Octavio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Moisan, Sabine. Institut National de Recherche en Informatique et en Automatique; Francia
Fil: Rigault, Jean-Paul. Institut National de Recherche en Informatique et en Automatique; Francia
description Background: Feature modeling has been widely used in domain engineering for thedevelopment and configuration of software product lines. A feature model represents the set of possible products or configurations to apply in a given context. Recently, this formalism has been applied to the runtime (re-)configuration of systems with high variability and running in changing contexts. These systems must adapt by updating their component assembly configuration at runtime, while minimizing the impact of such changes on the quality of service. For this reason the selection of a good system configuration is seen as an optimization problem based on quality attribute criteria.Methods:We propose an approach for system adaptation based on the specification,measurement and optimization of quality attribute properties on feature models.Furthermore, we describe its integration into a platform for supporting theself-adaptation of component-based systems. Feature models are annotated withquality attribute properties and metrics, and then an efficient algorithm is used to deal with the optimization problem.Results and conclusions:Two performance properties -- frame processing time andreconfiguration time -- are estimated with our model against measurements obtainedfrom the running system to show the accuracy of metrics on feature models forestimating quality attribute properties. The results show evidence that these metrics are reasonably accurate for measuring performance properties on a realistic component-based computer vision system.
publishDate 2015
dc.date.none.fl_str_mv 2015-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/58096
Sánchez, Luis Emiliano; Diaz Pace, Jorge Andres; Zunino Suarez, Alejandro Octavio; Moisan, Sabine; Rigault, Jean-Paul; An Approach Based on Feature Models and Quality Criteria for Adapting Component-Based Systems; Springer; Journal of Software Engineering Research and Development; 3; 10; 6-2015; 1-30
2195-1721
CONICET Digital
CONICET
url http://hdl.handle.net/11336/58096
identifier_str_mv Sánchez, Luis Emiliano; Diaz Pace, Jorge Andres; Zunino Suarez, Alejandro Octavio; Moisan, Sabine; Rigault, Jean-Paul; An Approach Based on Feature Models and Quality Criteria for Adapting Component-Based Systems; Springer; Journal of Software Engineering Research and Development; 3; 10; 6-2015; 1-30
2195-1721
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1186/s40411-015-0022-1
info:eu-repo/semantics/altIdentifier/doi/10.1186/s40411-015-0022-1
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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