Bibi, NaziaRana, TauseefMaqbool, AyeshaAfzal, FarkhandaAkguel, AliDe la sen, Manuel2024-12-242024-12-2420231424-8220https://doi.org/10.3390/s23010525https://hdl.handle.net/20.500.12604/8264The 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.eninfo:eu-repo/semantics/openAccesscode reuserecommendation systemscode recommendationcomponent-based software developmentintelligent decision support systemArticle231Q2WOS:000910102600001Q12-s2.0-851459755033661712210.3390/s23010525