Integrating Machine Learning and Model-Driven Engineering for User Interfaces: A Systematic Literature Review - Aguilar-Encarnacion, Pedro; Iñiguez-Jarrín, Carlos; Sandobalín, Julio (Anais do Congresso Ibero-Americano em Engenharia de Software (CIbSE), 2026)
User Interfaces (UI) operate in heterogeneous contexts and require adaptation and, in some cases, intelligent behavior. Machine Learning (ML) and Model-Driven Engineering (MDE) offer complementary capabilities to address this challenge; however, the evidence on their combined use in UI development remains fragmented. The literature still lacks an integrated synthesis of how ML and MDE are combined in this domain. This study aims to synthesize this evidence through a Systematic Literature Review conducted according to the guidelines of Kitchenham, Budgen, and Klotins. The findings cover UI typologies, ML roles and model families, MDE artefacts and paradigms, ML–MDE integration workflows, and coupling, and identify research gaps.