The development of automotive electronics and software systems is often associated with high costs due to their multi-domain nature (including control engineering, electronics, hydraulics, mechanics, etc). The involvement of these different disciplines makes it difficult for control engineers to test their controllers with them being integrated in the whole system, in early development phases. By introducing the "XiL approach", ETAS wants to leverage virtualization techniques in order to bring embedded systems to the desk of every developer. The XiL approach implies fast development cycles due to easy integration of software, vehicle and plant components on the PC. XiL strives for seamless transition between X-in-the-loop setups, with X representing any control model (M), software (S), or hardware (H) under test. This paper will outline this methodology with an engine management system example.

Model-based Systems Engineering plays a key role in the automotive industry by reducing the development costs while designing more complex controllers. Thanks to the continuous improvement of models accuracy and their computational performance, introducing system simulation in form of "in-the-loop" simulations in early stages of the development is possible. However, this is often limited by the efforts required to integrate and co-simulate heterogeneous models originating from different domains (e.g. electronic, mechanic, hybrid, etc). This work presents a standard-based integration, simulation and analysis solution leveraging the AUTomotive Open System ARchitecture (AUTOSAR) and the Functional Mockup Interface (FMI) [1] standard, and enabling a seamless transition from Model- to Software-in-the-loop simulations. Moreover, we demonstrate an accurate powertrain co-simulation based on the above-mentioned solution.

Much progress has been achieved in defining methods, techniques, and tools for software architecture reconstruction (SAR). However, less progress has been achieved in constructing reasoning frameworks from existing systems that support organizations in architecture analysis and design decisions. These reasoning frameworks are necessary, for example, to assemble existing components and deploy them in new system configurations. We propose a model-centric approach where this kind of reasoning is driven by the analysis of quality attribute scenarios. The scenarios and the related quality attribute models guide the SAR effort by focusing on the elicitation of model relevant artifacts. The approach further drives the model construction towards the analytical support of What If scenarios that explore responses stimulated by new requirements, such as new deployments of existing components. The paper provides two real-world case studies. The first case study introduces the model-centric reconstruction approach in the context of a large satellite tracking system. The second case study provides the construction of a time performance model for an existing embedded system in the automotive industry. The model allows us to perform cost-efficient predictions of component assemblies in new customer configurations. Copyright © 2005 John Wiley & Sons, Ltd.

Product lines evolve out of existing products. In order to evaluate the potential of creating a product line from existing products, it is necessary to 'mine' their architectures and analyze the commonalities and variabilities across those architectures. To manage the evaluation process in a disciplined way the paper introduces the MAP (Mining Architectures for Product Lines) method. MAP outlines a bottom-up approach for mining the architecture of the existing products, a top-down approach to mapping architectural styles and attributes onto the mined architectures and an approach to analyzing their commonalities and variabilities. It combines well-known architecture reconstruction and product line analysis techniques. A case study is presented showing the application of the method and its benefits are outlined.