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An Intelligent Platform for Software Component Mining and Retrieval.
Bibi, Nazia; Rana, Tauseef; Maqbool, Ayesha; Afzal, Farkhanda; Akgül, Ali; De la Sen, Manuel.
Afiliação
  • Bibi N; Department of Computer Software Engineering, National University of Sciences and Technology, Islamabad 44000, Pakistan.
  • Rana T; Department of Computer Software Engineering, National University of Sciences and Technology, Islamabad 44000, Pakistan.
  • Maqbool A; Department of Computer Software Engineering, National University of Sciences and Technology, Islamabad 44000, Pakistan.
  • Afzal F; Department of Humanities and Basic Sciences, National Universityof Sciences and Technology, Islamabad 44000, Pakistan.
  • Akgül A; Departmentof Computer Science and Mathematics, Lebanese American University, Beirut 1102 2801, Lebanon.
  • De la Sen M; Department of Mathematics, Art and Science Faculty, Siirt University, Siirt 56100, Turkey.
Sensors (Basel) ; 23(1)2023 Jan 03.
Article em En | MEDLINE | ID: mdl-36617122
The 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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Interface Usuário-Computador / Software Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Paquistão País de publicação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Interface Usuário-Computador / Software Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Paquistão País de publicação: Suíça