Empirical studies for validating class diagram metrics

Autores
Genero, Marcela; Piattini, Mario; Calero, Coral
Año de publicación
2002
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The quality of class diagrams is crucial for all later design work and could be a major determinant for the quality of the software product that is finally delivered. In order to assess class diagram quality in an objective way it is necessary to have quantitative measurement instruments. This paper presents a set of metrics which measure UML class diagram structural complexity based on the use of UML relationships. Also it summarizes two controlled experiments carried out in order to corroborate if those metrics are related with UML class diagram maintainability. The findings obtained trough the experimentation reveal that most of the metrics we proposed (NAssoc, NAgg, NaggH, MaxHAgg, NGen, NgenH and MaxDIT) might be good indicators of class diagram maintainability. We cannot, however, draw such firm conclusions regarding the NDep metric.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
class diagram quality
tructural complexity
metrics
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:10915/183082
Acceder
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network_name_str SEDICI (UNLP)
spelling Empirical studies for validating class diagram metricsGenero, MarcelaPiattini, MarioCalero, CoralCiencias Informáticasclass diagram qualitytructural complexitymetricsThe quality of class diagrams is crucial for all later design work and could be a major determinant for the quality of the software product that is finally delivered. In order to assess class diagram quality in an objective way it is necessary to have quantitative measurement instruments. This paper presents a set of metrics which measure UML class diagram structural complexity based on the use of UML relationships. Also it summarizes two controlled experiments carried out in order to corroborate if those metrics are related with UML class diagram maintainability. The findings obtained trough the experimentation reveal that most of the metrics we proposed (NAssoc, NAgg, NaggH, MaxHAgg, NGen, NgenH and MaxDIT) might be good indicators of class diagram maintainability. We cannot, however, draw such firm conclusions regarding the NDep metric.Sociedad Argentina de Informática e Investigación Operativa2002-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf74-86http://sedici.unlp.edu.ar/handle/10915/183082enginfo:eu-repo/semantics/altIdentifier/issn/1666-1087info: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:UNLP2026-01-07T13:34:18Zoai:sedici.unlp.edu.ar:10915/183082Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292026-01-07 13:34:19.042SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Empirical studies for validating class diagram metrics
title Empirical studies for validating class diagram metrics
spellingShingle Empirical studies for validating class diagram metrics
Genero, Marcela
Ciencias Informáticas
class diagram quality
tructural complexity
metrics
title_short Empirical studies for validating class diagram metrics
title_full Empirical studies for validating class diagram metrics
title_fullStr Empirical studies for validating class diagram metrics
title_full_unstemmed Empirical studies for validating class diagram metrics
title_sort Empirical studies for validating class diagram metrics
dc.creator.none.fl_str_mv Genero, Marcela
Piattini, Mario
Calero, Coral
author Genero, Marcela
author_facet Genero, Marcela
Piattini, Mario
Calero, Coral
author_role author
author2 Piattini, Mario
Calero, Coral
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
class diagram quality
tructural complexity
metrics
topic Ciencias Informáticas
class diagram quality
tructural complexity
metrics
dc.description.none.fl_txt_mv The quality of class diagrams is crucial for all later design work and could be a major determinant for the quality of the software product that is finally delivered. In order to assess class diagram quality in an objective way it is necessary to have quantitative measurement instruments. This paper presents a set of metrics which measure UML class diagram structural complexity based on the use of UML relationships. Also it summarizes two controlled experiments carried out in order to corroborate if those metrics are related with UML class diagram maintainability. The findings obtained trough the experimentation reveal that most of the metrics we proposed (NAssoc, NAgg, NaggH, MaxHAgg, NGen, NgenH and MaxDIT) might be good indicators of class diagram maintainability. We cannot, however, draw such firm conclusions regarding the NDep metric.
Sociedad Argentina de Informática e Investigación Operativa
description The quality of class diagrams is crucial for all later design work and could be a major determinant for the quality of the software product that is finally delivered. In order to assess class diagram quality in an objective way it is necessary to have quantitative measurement instruments. This paper presents a set of metrics which measure UML class diagram structural complexity based on the use of UML relationships. Also it summarizes two controlled experiments carried out in order to corroborate if those metrics are related with UML class diagram maintainability. The findings obtained trough the experimentation reveal that most of the metrics we proposed (NAssoc, NAgg, NaggH, MaxHAgg, NGen, NgenH and MaxDIT) might be good indicators of class diagram maintainability. We cannot, however, draw such firm conclusions regarding the NDep metric.
publishDate 2002
dc.date.none.fl_str_mv 2002-09
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
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/10915/183082
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dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/1666-1087
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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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
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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