Taxonomía orientada a la interacción humano computador (HCI) en sistemas auto-adaptativos

Abstract

The digital era has transformed the interaction between humans and technology, driving the development of systems that not only respond to commands but also adapt to the changing needs of users. However, the complexity of these self-adaptive systems (SAs) and the diversity of contexts in which they operate present significant challenges for their effective implementation. Specifically, the lack of reference frameworks to guide the design and evaluation of human-computer interaction (HCI) in these systems limits their ability to enhance user experience and operational efficiency. This thesis directly addresses this gap by developing a specific taxonomy for HCI in SAs, providing a systematic framework to categorize and evaluate research and applications in this field. Additionally, a quality model in the domain of HCI in SAs is proposed, which assesses essential criteria such as functional suitability, performance efficiency, interaction capability, reliability, security, and flexibility. The validation of these proposals is carried out through the evaluation of the taxonomy’s understandability and the applicability of the quality model, using detailed analyses and systematic methodologies to ensure their relevance and effectiveness in software engineering. This approach provides a solid and organized framework for the development of HCI in SAs and new technologies.