A Framework for Analyzing Modeling Languages for Context-Aware Systems - Elyasaf, Achiya; Sturm, Arnon (SN computer science, 2023)
Context-aware systems keep on emerging in all of our daily activities. Context, which can be a location, a user, an actual activity, or physical conditions, plays a major role in such systems. Actually, everything we refer to in our systems can be considered as context. Mechanisms for managing context were devised to cope with this new situation, including frameworks and programming languages. However, modeling languages that address the notion of context are rare. In this paper, we aim to frame and further define the requirements for context modeling languages. Such a conceptualized framework sets the ground for designing and evaluating modeling languages for context-aware systems. We demonstrate a possible use of the proposed framework through the evaluation of context-oriented modeling languages: UML-based Context Modeling and Context-Oriented Live Sequence Chart (CO-LSC).