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As systems necessarily become more integrated and increasingly complex through market demands for more features, technical risks and therefore business risks increase. It becomes correspondingly harder to show that the properties desired of these Systems of Systems (SoS) actually hold under normal or abnormal operation. In particular, it is hard to detect emergent properties of a SoS because properties of individual systems are not necessarily compositional, especially during failure. This paper describes the objectives of a project addressing the problem of Dependable System of Systems and other related research in the field of Automotive Electronics. The capability being developed is based upon the scalable ‘Assumption-Commitment’[1] paradigm so that it can be applied to large and complex systems of systems.

This paper highlights and discusses the development and deployment of an enterprise-level tool infrastructure that fits into the production build environment of Ford Motor Company. A particular focus is on navigating bottlenecks and pitfalls that arise with the adoption of a model-based software development process. This includes provisions to support centralized data and architecture artifact management (including version control across the lifecycle of the software), support to integrate and manage legacy software artifacts, support to archive and bookshelf development milestones, and last but not least, built-in intelligence to spot potential sources of software defects early in the development stage.