Model Driven Approaches in System Development

(MDASD)

Model-Driven (MD) approaches have long enabled developers to specify systems at appropriate abstraction levels, separating design intent from platform-specific implementation details. By elevating models from documentation to primary development artifacts, MD approaches shift focus from low-level programming to higher-level modeling activities where software code, tests, configurations and other artefacts can be systematically generated from well-defined specifications. By providing shared, abstract, and semantically rich representations of systems, MD approaches also facilitate effective collaboration and communication among diverse stakeholders, including domain experts, developers, system engineers, and end users, thereby enabling their early and continuous participation throughout the development lifecycle.

In the AI era, MD approaches provide a structured framework for the design, development and optimization of complex systems by creating models that represent different system components, learning algorithms, neural networks and/or other components of a system. At the same time, adaptability is increased as the entire system can be updated quickly without having to rewrite large parts of the code, making it easier to integrate new functions or intelligent components.

This MD theme brings together researchers and practitioners working on model-driven approaches, techniques, and tools with applications across intelligent and information systems. Our goal is to foster experience sharing, spark new ideas, and advance the evaluation and dissemination of MD methodologies. We embrace the interdisciplinary nature of model-driven software development, welcoming contributions spanning Model Driven Software Engineering (MDSE), Model Driven Development (MDD), Domain Specific Modeling (DSM), and OMG's Model Driven Architecture (MDA). Beyond exploring MD applications in intelligent systems, we particularly encourage work addressing a critical contemporary challenge: how to effectively deploy modern AI and ML techniques within software development processes using the full spectrum of MD approaches.