Towards recovering architectural information from images of architectural diagrams

Autores
Maggiori, Emmanuel; Gervasoni, Luciano; Antúnez, Matías; Rago, Alejandro; Díaz Pace, J. Andrés
Año de publicación
2014
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The architecture of a software system is often described with diagrams embedded in the documentation. However, these diagrams are normally stored and shared as images, losing track of model-level architectural information and refraining software engineers from working on the architectural model later on. In this context, tools able to extract architectural information from images can be of great help. In this article, we present a framework called IMEAV for processing architectural diagrams (based on speci c viewtypes) and recovering information from them. We have instantiated our framework to analyze \\module views and evaluated this prototype with an image dataset. Results have been encouraging, showing a good accuracy for recognizing modules, relations and textual features.
XV Simposio Argentino de Ingeniería de Software
Materia
Ciencias de la Computación
framework
IMEAV
software architecture
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/4.0/
Repositorio
CIC Digital (CICBA)
Institución
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
OAI Identificador
oai:digital.cic.gba.gob.ar:11746/3410
Acceder
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network_acronym_str CICBA
repository_id_str 9441
network_name_str CIC Digital (CICBA)
spelling Towards recovering architectural information from images of architectural diagramsMaggiori, EmmanuelGervasoni, LucianoAntúnez, MatíasRago, AlejandroDíaz Pace, J. AndrésCiencias de la ComputaciónframeworkIMEAVsoftware architectureThe architecture of a software system is often described with diagrams embedded in the documentation. However, these diagrams are normally stored and shared as images, losing track of model-level architectural information and refraining software engineers from working on the architectural model later on. In this context, tools able to extract architectural information from images can be of great help. In this article, we present a framework called IMEAV for processing architectural diagrams (based on speci c viewtypes) and recovering information from them. We have instantiated our framework to analyze \\module views and evaluated this prototype with an image dataset. Results have been encouraging, showing a good accuracy for recognizing modules, relations and textual features.XV Simposio Argentino de Ingeniería de Software2014-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/3410enginfo:eu-repo/semantics/altIdentifier/issn/1850-2792info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-09-04T09:43:54Zoai:digital.cic.gba.gob.ar:11746/3410Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412025-09-04 09:43:55.089CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse
dc.title.none.fl_str_mv Towards recovering architectural information from images of architectural diagrams
title Towards recovering architectural information from images of architectural diagrams
spellingShingle Towards recovering architectural information from images of architectural diagrams
Maggiori, Emmanuel
Ciencias de la Computación
framework
IMEAV
software architecture
title_short Towards recovering architectural information from images of architectural diagrams
title_full Towards recovering architectural information from images of architectural diagrams
title_fullStr Towards recovering architectural information from images of architectural diagrams
title_full_unstemmed Towards recovering architectural information from images of architectural diagrams
title_sort Towards recovering architectural information from images of architectural diagrams
dc.creator.none.fl_str_mv Maggiori, Emmanuel
Gervasoni, Luciano
Antúnez, Matías
Rago, Alejandro
Díaz Pace, J. Andrés
author Maggiori, Emmanuel
author_facet Maggiori, Emmanuel
Gervasoni, Luciano
Antúnez, Matías
Rago, Alejandro
Díaz Pace, J. Andrés
author_role author
author2 Gervasoni, Luciano
Antúnez, Matías
Rago, Alejandro
Díaz Pace, J. Andrés
author2_role author
author
author
author
dc.subject.none.fl_str_mv Ciencias de la Computación
framework
IMEAV
software architecture
topic Ciencias de la Computación
framework
IMEAV
software architecture
dc.description.none.fl_txt_mv The architecture of a software system is often described with diagrams embedded in the documentation. However, these diagrams are normally stored and shared as images, losing track of model-level architectural information and refraining software engineers from working on the architectural model later on. In this context, tools able to extract architectural information from images can be of great help. In this article, we present a framework called IMEAV for processing architectural diagrams (based on speci c viewtypes) and recovering information from them. We have instantiated our framework to analyze \\module views and evaluated this prototype with an image dataset. Results have been encouraging, showing a good accuracy for recognizing modules, relations and textual features.
XV Simposio Argentino de Ingeniería de Software
description The architecture of a software system is often described with diagrams embedded in the documentation. However, these diagrams are normally stored and shared as images, losing track of model-level architectural information and refraining software engineers from working on the architectural model later on. In this context, tools able to extract architectural information from images can be of great help. In this article, we present a framework called IMEAV for processing architectural diagrams (based on speci c viewtypes) and recovering information from them. We have instantiated our framework to analyze \\module views and evaluated this prototype with an image dataset. Results have been encouraging, showing a good accuracy for recognizing modules, relations and textual features.
publishDate 2014
dc.date.none.fl_str_mv 2014-09
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv https://digital.cic.gba.gob.ar/handle/11746/3410
url https://digital.cic.gba.gob.ar/handle/11746/3410
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/1850-2792
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:CIC Digital (CICBA)
instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
instacron:CICBA
reponame_str CIC Digital (CICBA)
collection CIC Digital (CICBA)
instname_str Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
instacron_str CICBA
institution CICBA
repository.name.fl_str_mv CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
repository.mail.fl_str_mv marisa.degiusti@sedici.unlp.edu.ar
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