Migrating legacy web applications

Autores
Cajas, Viviana Elizabeth; Urbieta, Matías; Rossi, Gustavo Héctor; Rybarczyk, Yvez
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión aceptada
Descripción
Applications are a ubiquitous tool when running on mobile devices become an opportunity for a new digital business model. However, enterprises implemented the core business in legacy applications that are not designed to run properly on mobile devices. Consequently, this migration involves time and cost. The main contribution of this study to these limitations is an approach to assist this migration based on Markov chains that is a predictive user behaviour method that allows that available functionality is prioritized, the experience of User Interface is re-thought, and the new design is evaluated with a preliminary running version of the legacy app. An experiment on ten participants shows that a dynamic user interface that implements the Markov model provides the users with better usability, evidenced with an improvement of productivity labour and the Nielsen heuristics comparison between versions. This work suggests this model makes possible a smart and proactive interface design.
Materia
Ciencias de la Computación e Información
IFML
Markov chains
Legacy adaptatio
Mobile devices
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/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:11746/10675
Acceder
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network_acronym_str CICBA
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network_name_str CIC Digital (CICBA)
spelling Migrating legacy web applicationsCajas, Viviana ElizabethUrbieta, MatíasRossi, Gustavo HéctorRybarczyk, YvezCiencias de la Computación e InformaciónIFMLMarkov chainsLegacy adaptatioMobile devicesApplications are a ubiquitous tool when running on mobile devices become an opportunity for a new digital business model. However, enterprises implemented the core business in legacy applications that are not designed to run properly on mobile devices. Consequently, this migration involves time and cost. The main contribution of this study to these limitations is an approach to assist this migration based on Markov chains that is a predictive user behaviour method that allows that available functionality is prioritized, the experience of User Interface is re-thought, and the new design is evaluated with a preliminary running version of the legacy app. An experiment on ten participants shows that a dynamic user interface that implements the Markov model provides the users with better usability, evidenced with an improvement of productivity labour and the Nielsen heuristics comparison between versions. This work suggests this model makes possible a smart and proactive interface design.2019info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/10675enginfo:eu-repo/semantics/altIdentifier/doi/10.1007/s10586-020-03147-6info:eu-repo/semantics/altIdentifier/issn/1573-7543info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-10-16T09:27:34Zoai:digital.cic.gba.gob.ar:11746/10675Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412025-10-16 09:27:34.315CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse
dc.title.none.fl_str_mv Migrating legacy web applications
title Migrating legacy web applications
spellingShingle Migrating legacy web applications
Cajas, Viviana Elizabeth
Ciencias de la Computación e Información
IFML
Markov chains
Legacy adaptatio
Mobile devices
title_short Migrating legacy web applications
title_full Migrating legacy web applications
title_fullStr Migrating legacy web applications
title_full_unstemmed Migrating legacy web applications
title_sort Migrating legacy web applications
dc.creator.none.fl_str_mv Cajas, Viviana Elizabeth
Urbieta, Matías
Rossi, Gustavo Héctor
Rybarczyk, Yvez
author Cajas, Viviana Elizabeth
author_facet Cajas, Viviana Elizabeth
Urbieta, Matías
Rossi, Gustavo Héctor
Rybarczyk, Yvez
author_role author
author2 Urbieta, Matías
Rossi, Gustavo Héctor
Rybarczyk, Yvez
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias de la Computación e Información
IFML
Markov chains
Legacy adaptatio
Mobile devices
topic Ciencias de la Computación e Información
IFML
Markov chains
Legacy adaptatio
Mobile devices
dc.description.none.fl_txt_mv Applications are a ubiquitous tool when running on mobile devices become an opportunity for a new digital business model. However, enterprises implemented the core business in legacy applications that are not designed to run properly on mobile devices. Consequently, this migration involves time and cost. The main contribution of this study to these limitations is an approach to assist this migration based on Markov chains that is a predictive user behaviour method that allows that available functionality is prioritized, the experience of User Interface is re-thought, and the new design is evaluated with a preliminary running version of the legacy app. An experiment on ten participants shows that a dynamic user interface that implements the Markov model provides the users with better usability, evidenced with an improvement of productivity labour and the Nielsen heuristics comparison between versions. This work suggests this model makes possible a smart and proactive interface design.
description Applications are a ubiquitous tool when running on mobile devices become an opportunity for a new digital business model. However, enterprises implemented the core business in legacy applications that are not designed to run properly on mobile devices. Consequently, this migration involves time and cost. The main contribution of this study to these limitations is an approach to assist this migration based on Markov chains that is a predictive user behaviour method that allows that available functionality is prioritized, the experience of User Interface is re-thought, and the new design is evaluated with a preliminary running version of the legacy app. An experiment on ten participants shows that a dynamic user interface that implements the Markov model provides the users with better usability, evidenced with an improvement of productivity labour and the Nielsen heuristics comparison between versions. This work suggests this model makes possible a smart and proactive interface design.
publishDate 2019
dc.date.none.fl_str_mv 2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://digital.cic.gba.gob.ar/handle/11746/10675
url https://digital.cic.gba.gob.ar/handle/11746/10675
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1007/s10586-020-03147-6
info:eu-repo/semantics/altIdentifier/issn/1573-7543
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/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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