Recommender Systems in Model-Driven Engineering: A Systematic Mapping Review





Publicado en

Actas de las XXVI Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2022)

Licencia Creative Commons


Recommender systems are information filtering systems used in many online applications like music and video broadcasting and e-commerce platforms, and they are also increasingly applied to facilitate software engineering activities. Following this trend, we are witnessing a growing research interest on recommendation approaches that assist with modelling tasks and model-based development processes. In this paper, we report on a systematic mapping review that classifies the existing research work on recommender systems for model-driven engineering (MDE). This study aims to serve as a guide for tool builders and researchers in understanding the MDE tasks that might be subject to recommendations, the applicable recommendation techniques and evaluation methods, and the open challenges and opportunities in this field of research.


Acerca de Almonte, Lissette

Palabras clave

Model-Driven Engineering, Recommender Systems, Systematic Mapping Review
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