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dc.contributor.authorBibi, Nazia
dc.contributor.authorRana, Tauseef
dc.contributor.authorMaqbool, Ayesha
dc.contributor.authorAfzal, Farkhanda
dc.contributor.authorAkgül, Ali
dc.contributor.authorDe la Sen Parte, Manuel ORCID
dc.date.accessioned2023-01-10T17:44:57Z
dc.date.available2023-01-10T17:44:57Z
dc.date.issued2023-01-03
dc.identifier.citationSensors 23(1) : (2023) // Article ID 525es_ES
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/10810/59214
dc.description.abstractThe development of robotic applications necessitates the availability of useful, adaptable, and accessible programming frameworks. Robotic, IoT, and sensor-based systems open up new possibilities for the development of innovative applications, taking advantage of existing and new technologies. Despite much progress, the development of these applications remains a complex, time-consuming, and demanding activity. Development of these applications requires wide utilization of software components. In this paper, we propose a platform that efficiently searches and recommends code components for reuse. To locate and rank the source code snippets, our approach uses a machine learning approach to train the schema. Our platform uses trained schema to rank code snippets in the top k results. This platform facilitates the process of reuse by recommending suitable components for a given query. The platform provides a user-friendly interface where developers can enter queries (specifications) for code search. The evaluation shows that our platform effectively ranks the source code snippets and outperforms existing baselines. A survey is also conducted to affirm the viability of the proposed methodology.es_ES
dc.description.sponsorshipThis research was funded by the Basque Government through grants IT1555-22 and KK-2022/00090; and to MCIN/AEI 269.10.13039/501100011033 for grant PID2021-1235430B-C21/C22.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectcode reusees_ES
dc.subjectrecommendation systemses_ES
dc.subjectcode recommendationes_ES
dc.subjectcomponent-based software developmentes_ES
dc.subjectintelligent decision support systemes_ES
dc.titleAn Intelligent Platform for Software Component Mining and Retrievales_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.date.updated2023-01-06T13:52:59Z
dc.rights.holder© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).es_ES
dc.relation.publisherversionhttps://www.mdpi.com/1424-8220/23/1/525es_ES
dc.identifier.doi10.3390/s23010525
dc.departamentoesElectricidad y electrónica
dc.departamentoeuElektrizitatea eta elektronika


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© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).