Systems & Software Engineering
Understand complex systems, connect engineering disciplines and validate behaviour earlier, with model-based and model-driven engineering.
From complexity to clarity
See the whole system. Test your thinking earlier.
Mechanical, electrical and software decisions influence one another. When requirements, architecture and behaviour are disconnected, teams struggle to see the consequences of change. Models create a shared engineering context, making complex interactions easier to discuss, assess and refine.
What changes for your team
From diagrams to executable behaviour
Earlier feedback, clearer evidence
System development maturity levels
Where are you today, and what is your next useful step?
From an idea that is difficult to communicate to a model whose behaviour can be examined: the System Development Maturity Levels describe seven ways to make engineering knowledge more explicit, executable and testable.
Use it as a discussion framework, not a race to the final stage. Choose a useful next step for your product, risks and team. Tools support the practice; owning a tool does not establish a maturity level.
01
Idea
An initial idea is not yet formalised and can be difficult to communicate. Capture it so others can explore it with you.
Mind mapping and shared exploration
02
Linear text
Describe the idea in a document others can read and review. The intent is explicit, but relationships still need interpretation.
Document-based description
03
Structured text
Organise the description around requirements, attributes and relationships, making individual needs easier to manage and trace.
Requirements management · IBM DOORS
04
Descriptive model
Represent architecture, interfaces and behaviour with diagrams and text. A shared model makes the system structure easier to discuss.
System modelling · IBM Engineering Rhapsody
05
Executable model
Run and simulate the model so the team can observe how the system behaves and explore interactions before implementation.
Simulation · IBM Engineering Rhapsody
06
Validated model
Define tests for the intended behaviour and check the model against them. Make the test scope and validation evidence explicit.
Model-based testing and test execution
07
Proven model
Investigate unintended behaviour with systematic verification and generated tests, within explicit assumptions and verification scope.
Test generation and verification
The taxonomy is discipline-independent: mechanical engineering, software, analogue and digital electronics, and optics can use the same progression to discuss their engineering practice.
“Proven model” is the source taxonomy’s stage name, not a guarantee of defect-free software or safety certification. Conclusions depend on the model, verification method and coverage.
Towards the digital twin
Make virtual exploration useful before going further
Executable, validated models can support virtual experimentation and digital-twin development. The appropriate next step depends on what your model represents, which questions you need to answer and how it connects to your engineering environment.
Methods, tools and team capability
Explore UML and SysML, systems and software engineering methods, Rhapsody training, guidance and workshops, alongside the tools that connect requirements, models and tests.
Find your next engineering step
Bring your product challenges, existing models and tool context. Start with a 15-minute call.