Context - The Internet of Things (IoT) refers to a distributed network of smart, connected devices that collaboratively sense, process, and act upon real-world environments. Designing such systems requires managing complex architectural concerns spanning software logic, hardware configuration, and spatial deployment, as well as validating non-functional properties like energy consumption and communication efficiency. Objective - To provide a unified, architecture-centric framework that supports the description, simulation, and automated code generation of IoT applications across software, hardware, and physical space dimensions. Method - We use Model Driven Engineering(MDE) approaches to develop CAPS, a framework that uniquely integrates multi-view architectural modeling, energy- and traffic-aware simulation via CupCarbon, and seamless generation of deployable Arduino code from high-level design models. Result - CAPS enables a traceable and cohesive development process from architectural design to physical deployment. Case studies from diverse domains demonstrate its ability to improve modeling expressiveness, maintain transformation fidelity, and reduce development time through automation. Conclusion - CAPS unifies architectural modeling, simulation, and code generation into a novel, end-to-end toolchain, addressing fragmentation in the IoT development lifecycle and enhancing early validation and traceability.

Mobile applications may benefit from context awareness since they incur to context changes during their execution and their success depends on the user perceived quality. Context awareness requires context monitoring and system adaptation, these two tasks are very expensive especially in mobile applications. Our research aims at developing a methodology that enables effective context awareness techniques for mobile applications that allows adaptations of the mobile app to context changes so that the desired system quality properties and user satisfaction is maximized. Here effective means selecting a minimum set of context variables to monitor and a minimum set of adaptive tactics to inject into mobile applications that allows to guarantee the required software quality and to maximize the user satisfaction. In this paper, we show the devised methodology on a motivating example, detailing the ongoing work.