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Combining Multiple Granularity Variability in a Software Product Line Approach for Web Engineering
dc.contributor.author | Horcas Aguilera, José Miguel | |
dc.contributor.author | Cortiñas, Alejandro | |
dc.contributor.author | Fuentes, Lidia | |
dc.contributor.author | Rodríguez Luaces, Miguel | |
dc.date.accessioned | 2022-07-12T17:22:52Z | |
dc.date.available | 2022-07-12T17:22:52Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | HORCAS, Jose-Miguel, CORTIÑAS, Alejandro, FUENTES, Lidia and LUACES, Miguel R., 2022. Combining multiple granularity variability in a software product line approach for web engineering. Information and Software Technology. 2022. Vol. 148, p. 106910. DOI https://doi.org/10.1016/j.infsof.2022.106910 | es_ES |
dc.identifier.uri | http://hdl.handle.net/2183/31170 | |
dc.description.abstract | [Abstract] Context: Web engineering involves managing a high diversity of artifacts implemented in different languages and with different levels of granularity. Technological companies usually implement variable artifacts of Software Product Lines (SPLs) using annotations, being reluctant to adopt hybrid, often complex, approaches combining composition and annotations despite their benefits. Objective: This paper proposes a combined approach to support fine and coarse-grained variability for web artifacts. The proposal allows web developers to continue using annotations to handle fine-grained variability for those artifacts whose variability is very difficult to implement with a composition-based approach, but obtaining the advantages of the composition-based approach for the coarse-grained variable artifacts. Methods: A combined approach based on feature modeling that integrates annotations into a generic composition-based approach. We propose the definition of compositional and annotative variation points with custom-defined semantics, which is resolved by a scaffolding-based derivation engine. The approach is evaluated on a real-world web-based SPL by applying a set of variability metrics, as well as discussing its quality criteria in comparison with annotations, compositional, and combined existing approaches. Results: Our approach effectively handles both fine and coarse-grained variability. The mapping between the feature model and the web artifacts promotes the traceability of the features and the uniformity of the variation points regardless of the granularity of the web artifacts. Conclusions: Using well-known techniques of SPLs from an architectural point of view, such as feature modeling, can improve the design and maintenance of variable web artifacts without the need of introducing complex approaches for implementing the underlying variability. | es_ES |
dc.description.sponsorship | The work of the authors from the Universidad de Málaga is supported by the projects Magic P12-TIC1814 (post-doctoral research grant), MEDEA RTI2018-099213-B-I00 (co-financed by FEDER funds), Rhea P18-FR-1081 (MCI/AEI/FEDER, UE), LEIA UMA18-FEDERIA-157, TASOVA MCIU-AEI TIN2017-90644-REDT and, European Union’s H2020 research and innovation program under grant agreement DAEMON 101017109. The work of the authors from the Universidade da Coruña has been funded by MCIN/AEI/10.13039/501100011033, NextGenerationEU/PRTR, FLATCITY-POC: PDC2021-121239-C31 ; MCIN/AEI/10.13039/501100011033 EXTRACompact: PID2020-114635RB-I00 ; GAIN/Xunta de Galicia/ERDF CEDCOVID: COV20/00604 ; Xunta de Galicia/FEDER-UE GRC: ED431C 2021/53 ; MICIU/FEDER-UE BIZDEVOPSGLOBAL: RTI-2018-098309-B-C32 ; MCIN/AEI/10.13039/501100011033 MAGIST: PID2019-105221RB-C41 | es_ES |
dc.description.sponsorship | Junta de Andalucía; P12-TIC-1814 | es_ES |
dc.description.sponsorship | Universidad de Málaga; UMA18-FEDERIA-157 | es_ES |
dc.description.sponsorship | Xunta de Galicia; COV20/00604 | |
dc.description.sponsorship | Xunta de Galicia; ED431C 2021/53 | |
dc.description.sponsorship | Junta de Andalucía; P18-FR-1081 | |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/101017109 | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-099213-B-I00/ES/MEDEA: METODOS Y HERRAMIENTAS PARA EL DESPLIEGUE DE APLICACIONES ECO-EFICIENTES EN EL EDGE/ | |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-90644-REDT/ES/RED EN NUEVAS TENDENCIAS EN ARQUITECTURA SOFTWARE Y VARIABILIDAD/ | |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PDC2021-121239-C31/ES/ | |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-114635RB-I00/ES/EXPLOTACION ENRIQUECIDA DE TRAYECTORIAS CON ESTRUCTURAS DE DATOS COMPACTAS Y GIS/ | |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI-2018-098309-B-C32/ES/BIZDEVOPS-GLOBAL: UN FRAMEWORK TECNOLOGICO Y METODOLOGICO SOSTENIBLE PARA EL DESARROLLO DE SOFTWARE ALINEADO CON EL NEGOCIO EN DEVOPS GLOBAL/ | |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-105221RB-C41/ES/VISUALIZACION Y EXPLORACION BASADA EN FLUJOS Y ANALITICA DE BIG DATA ESPACIAL/ | |
dc.relation.uri | https://doi.org/10.1016/j.infsof.2022.106910 | es_ES |
dc.rights | Atribución 4.0 Internacional | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | Annotations | es_ES |
dc.subject | Composition | es_ES |
dc.subject | Feature models | es_ES |
dc.subject | SPL | es_ES |
dc.subject | Variability | es_ES |
dc.subject | Web engineering | es_ES |
dc.title | Combining Multiple Granularity Variability in a Software Product Line Approach for Web Engineering | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Information and Software Technology | es_ES |
UDC.volume | 148 | es_ES |
UDC.startPage | 106910 | es_ES |
dc.identifier.doi | 10.1016/j.infsof.2022.106910 |
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