Emotion-Driven Adaptation of Software Applications using User Requirements Notation Models
Abstract
Software applications aim to deliver intuitive user experiences that maximize adoption and effectiveness. However, accommodating individual differences poses challenges for universally accessible interface design. This paper proposes an emotion-driven adaptation approach to develop Adaptive user interface applications (AUIs) using User Requirements Notation (URN) Models. The approach focuses on eliciting emotional requirements, designing alternative adaptation strategies, and implementing dynamic UI adaptations based on user emotions. During the requirements phase, user emotional goals are elicited to construct emotion-aware goal models using Goal-oriented Requirements Language (GRL). These models are subsequently analyzed to inform the development of adaptation strategies for the interface at runtime, which are triggered by transitions in emotional states. Specifically, User Case Maps (UCMs) capture adaptive strategies that are enacted according to users' emotions inferred through interaction monitoring. The technique provides a flexible, requirements-driven methodology applicable across domains like healthcare, education, or finance that demands accommodating diverse individual differences and delivering optimized user experiences.