Engineering recommender systems for modelling languages: Concept, tool and evaluation

Recommender systems (RSs) are ubiquitous in all sorts of online applications, in areas like shopping, media broadcasting, travel and tourism, among many others. They are also common to help in software engineering tasks, including software modelling, where we are recently witnessing proposals to enr...

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Detalhes bibliográficos
Autores: Almonte García, Lissette, Guerra Sánchez, Esther, Cantador Gutiérrez, Iván, Lara Jaramillo, Juan de
Formato: artículo
Fecha de publicación:2024
País:España
Recursos:Universidad Autónoma de Madrid
Repositorio:Biblos-e Archivo. Repositorio Institucional de la UAM
Idioma:inglés
OAI Identifier:oai:repositorio.uam.es:10486/713445
Acesso em linha:http://hdl.handle.net/10486/713445
https://dx.doi.org/10.1007/s10664-024-10483-3
Access Level:acceso abierto
Palavra-chave:Domain-Specific Languages
Model-Driven Engineering
Modelling Languages
Recommender Systems
User Study
Informática
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spelling Engineering recommender systems for modelling languages: Concept, tool and evaluationAlmonte García, LissetteGuerra Sánchez, EstherCantador Gutiérrez, IvánLara Jaramillo, Juan deDomain-Specific LanguagesModel-Driven EngineeringModelling LanguagesRecommender SystemsUser StudyInformáticaRecommender systems (RSs) are ubiquitous in all sorts of online applications, in areas like shopping, media broadcasting, travel and tourism, among many others. They are also common to help in software engineering tasks, including software modelling, where we are recently witnessing proposals to enrich modelling languages and environments with RSs. Modelling recommenders assist users in building models by suggesting items based on previous solutions to similar problems in the same domain. However, building a RS for a modelling language requires considerable effort and specialised knowledge. To alleviate this problem, we propose an automated, model-driven approach to create RSs for modelling languages. The approach provides a domain-specific language called Droid to configure every aspect of the RS: the type of the recommended modelling elements, the gathering and preprocessing of training data, the recommendation method, and the metrics used to evaluate the created RS. The RS so configured can be deployed as a service, and we offer out-of-the-box integration with Eclipse modelling editors. Moreover, the language is extensible with new data sources and recommendation methods. To assess the usefulness of our proposal, we report on two evaluations. The first one is an offline experiment measuring the precision, completeness and diversity of recommendations generated by several methods. The second is a user study – with 40 participants – to assess the perceived quality of the recommendations. The study also contributes with a novel evaluation methodology and metrics for RSs in model-driven engineeringThis project has received funding from the EU Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813884, and from the Spanish Ministry of Science (projects TED2021-129381B-C21, PID2021-122270OB-I00, PID2019-108965GB-I00, and RED2022-134647-T)SpringerDepartamento de Ingeniería InformáticaEscuela Politécnica Superior20242024-06-18research articlehttp://purl.org/coar/resource_type/c_2df8fbb1VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10486/713445https://dx.doi.org/10.1007/s10664-024-10483-3reponame:Biblos-e Archivo. Repositorio Institucional de la UAMinstname:Universidad Autónoma de MadridInglésengEuropean Commission http://dx.doi.org/10.13039/501100000780 Horizon 2020 Framework Programme 813884open accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:repositorio.uam.es:10486/7134452026-06-23T12:46:27Z
dc.title.none.fl_str_mv Engineering recommender systems for modelling languages: Concept, tool and evaluation
title Engineering recommender systems for modelling languages: Concept, tool and evaluation
spellingShingle Engineering recommender systems for modelling languages: Concept, tool and evaluation
Almonte García, Lissette
Domain-Specific Languages
Model-Driven Engineering
Modelling Languages
Recommender Systems
User Study
Informática
title_short Engineering recommender systems for modelling languages: Concept, tool and evaluation
title_full Engineering recommender systems for modelling languages: Concept, tool and evaluation
title_fullStr Engineering recommender systems for modelling languages: Concept, tool and evaluation
title_full_unstemmed Engineering recommender systems for modelling languages: Concept, tool and evaluation
title_sort Engineering recommender systems for modelling languages: Concept, tool and evaluation
dc.creator.none.fl_str_mv Almonte García, Lissette
Guerra Sánchez, Esther
Cantador Gutiérrez, Iván
Lara Jaramillo, Juan de
author Almonte García, Lissette
author_facet Almonte García, Lissette
Guerra Sánchez, Esther
Cantador Gutiérrez, Iván
Lara Jaramillo, Juan de
author_role author
author2 Guerra Sánchez, Esther
Cantador Gutiérrez, Iván
Lara Jaramillo, Juan de
author2_role author
author
author
dc.contributor.none.fl_str_mv Departamento de Ingeniería Informática
Escuela Politécnica Superior
dc.subject.none.fl_str_mv Domain-Specific Languages
Model-Driven Engineering
Modelling Languages
Recommender Systems
User Study
Informática
topic Domain-Specific Languages
Model-Driven Engineering
Modelling Languages
Recommender Systems
User Study
Informática
description Recommender systems (RSs) are ubiquitous in all sorts of online applications, in areas like shopping, media broadcasting, travel and tourism, among many others. They are also common to help in software engineering tasks, including software modelling, where we are recently witnessing proposals to enrich modelling languages and environments with RSs. Modelling recommenders assist users in building models by suggesting items based on previous solutions to similar problems in the same domain. However, building a RS for a modelling language requires considerable effort and specialised knowledge. To alleviate this problem, we propose an automated, model-driven approach to create RSs for modelling languages. The approach provides a domain-specific language called Droid to configure every aspect of the RS: the type of the recommended modelling elements, the gathering and preprocessing of training data, the recommendation method, and the metrics used to evaluate the created RS. The RS so configured can be deployed as a service, and we offer out-of-the-box integration with Eclipse modelling editors. Moreover, the language is extensible with new data sources and recommendation methods. To assess the usefulness of our proposal, we report on two evaluations. The first one is an offline experiment measuring the precision, completeness and diversity of recommendations generated by several methods. The second is a user study – with 40 participants – to assess the perceived quality of the recommendations. The study also contributes with a novel evaluation methodology and metrics for RSs in model-driven engineering
publishDate 2024
dc.date.none.fl_str_mv 2024
2024-06-18
dc.type.none.fl_str_mv research article
http://purl.org/coar/resource_type/c_2df8fbb1
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10486/713445
https://dx.doi.org/10.1007/s10664-024-10483-3
url http://hdl.handle.net/10486/713445
https://dx.doi.org/10.1007/s10664-024-10483-3
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv European Commission http://dx.doi.org/10.13039/501100000780 Horizon 2020 Framework Programme 813884
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:Biblos-e Archivo. Repositorio Institucional de la UAM
instname:Universidad Autónoma de Madrid
instname_str Universidad Autónoma de Madrid
reponame_str Biblos-e Archivo. Repositorio Institucional de la UAM
collection Biblos-e Archivo. Repositorio Institucional de la UAM
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.228081

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