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0 7 4 0 -7 4 5 9 / 0 2 / $ 1 7 . 0 0 © 2 0 0 2 I E E E efficiency, while security systems protect the car from unauthorized manipulation.An automotive system typically consists of dedicated processors, software, and interfaces that let the system measure, manipulate, and otherwise interact with its external environment. Designers optimize such systems to reflect specific application characteristics. Apart from a system's desired functionality, automotive system designers must consider many possibly conflicting qualities and constraints. Developing an automotive system can thus involve hundreds or thousands of variants, adding to the existing engineering complexity. Whereas variability has typically been addressed on a case-by-case basis in late development phases, designers now need a managed, systematic approach to the ever-increasing number of variants.Product lines provide this systematic approach, along with a special focus on vari-ability among related products. As we discuss here, systematic planning and continuous variability management is a prerequisite for effective product lines. We've developed an approach to modeling and utilizing variability to support the efficient creation of product variants. Our approach is based on experiences with several industrial case studies at Bosch. Before describing them, we explain how product line development meets the major design challenges in the automotive system domain. Product line developmentAutomotive systems typically have thousands of requirements, but some are especially important. Many automotive systems are real-time systems with strict temporal requirements that result from the internal control loops. Thus, a computation's correctness depends, in part, on its timeliness.

Abstract

Product Derivation is one of the central activities in Software Product Lines (SPL). One of the main challenges of the process of product derivation is dealing with complexity, which is caused by the large number of artifacts and dependencies between them. Another major challenge is maximizing development efficiency and reducing time-to-market, while at the same time producing high quality products. One approach to overcome these challenges is to automate the derivation process. To this end, this paper focuses on one particular activity of the derivation process; the derivation of the product-specific architecture and describes how this activity can be automated using a model-driven approach. The approach derives the product-specific architecture by selectively copying elements from the product-line architecture. The decision, which elements are included in the derived architecture, is based on a product-specific feature configuration. We present a prototype that implements the derivation as a model transformation described in the Atlas Transformation Language (ATL). We conclude with a short overview of related work and directions for future research.

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