Models have become essential for understanding the structure and behavior of complex systems. Modeling helps in simulation and early validation and is a fundamental part of engineering. It is an effective way to manage the complexity of system and software development, enabling communication, design and assessment of requirements, architectures, systems and software. That's why the industry is moving towards Model Based Systems Engineering (MBSE). However, there is more to MBSE: executable models leading to Model Driven Systems Engineering (MDSE).
MDSE leverages graphical models and pre-built application components so that users not only can visually construct but also virtually interact with the system and test their complex systems through executable graphical models. As such, the models not only contribute to a better understanding of structure and behavior, but also help understand the system more clearly earlier on in the development phase. As a result, models increase the ability to improve and validate ideas and concepts as early as possible in the process when it costs less to adapt.
An effective approach to drive the challenging tasks of improving Systems Engineering in a structured way is the Systems Development Taxonomy. This classification has been established based on many different domains, projects and customers. It determines seven practice stages and also helps in laying out a path for the incremental adoption of MDSE within an organization.