Supporting model evolution in model-driven development of automotive embedded system

Abstract: Innovative functions in cars, such as active safety systems and advanced driver assistance systems, are realized as embedded systems. The development of such automotive embedded systems is challenging in several respects: the product typically has several crosscutting system properties, experts of diverse disciplines need to cooperate and appropriate processes and tools are required to improve the effciency and the complexity management of development. Model-driven development captures the architecture of the embedded system in the form of models with well-defined metamodels. Model-driven development provides a partial solution to some of the challenges of embedded systems development, but it also introduces new challenges. Models do not remain static, but they change over time and evolve. Evolution can change models in two ways: (1) by making design decisions and adding, deleting or changing model elements, or (2) by reusing models in different tools. We propose support for both aspects of model evolution. (1) When models are changed, the design decisions and the justification for the change are usually neither captured nor documented in a systematic way. As a result, important information about the model is lost, making the model more difficult to understand, which hampers model evolution and maintenance. To support model evolution, design decisions need to be captured explicitly using an appropriate representation. This representation reduces the overhead of capturing design decisions, keeps the model and the design decision documentation consistent and links the design decision documentation to the model. As a result, the captured design decisions provide a record of the model evolution and the rationale of the evolution. (2) Several models and views are used to describe an embedded system in different life cycle stages and from the viewpoints of the involved disciplines. To create the various models, a number of specialized development tools are used. These tools are usually disconnected, so the models cannot be transferred between different tools. Thus, models may become inconsistent, which hampers understandability of the models and increases the cost of development. We present a model-based tool integration approach that uses a common metamodel in combination with model transformation technology to build bridges between different development tools. We apply this approach in a case study and integrate several tools for automotive embedded systems development: A systems engineering tool, a safety engineering tool and a simulation tool. As a part of future work, we plan to extend the tool integration approach to exchange not only models but also the attached documentation of design decisions. As a result, the design decision documentation is linked consistently to corresponding model elements of the various tool-specific models, supporting model evolution across several development tools