Centralized Lifecycle Management of Model-Based Software Artifacts

Paper #:
  • 2017-01-0009

Published:
  • 2017-03-28
Abstract:
The reception of automobiles in the marketplace is more and more driven by the appeal of software related features such as infotainment features, advanced powertrain control features, collision avoidance features, etc. Simultaneously, it has become commonplace to develop software artifacts in decentralized locations. As a consequence, embedded automotive software systems have become increasingly complex and the proper management of software artifacts over the lifetime of a vehicle is increasingly difficult. However, recalls are costly, and hence it is imperative that the developed software is error free, despite its complexity and despite coordination challenges. These challenges give rise to the need for enterprise-level tools to support a unified and guided software development process. This process is commonly formulated around the principles of a model-based software development paradigm. Within this development framework, issues that require specific attention include the management and development of shared model artifacts, the management and specification of shared data definitions, the management and enforcement of uniform conventions (naming conventions, use of units, specification of variants, etc.), and the verification of data integrity between all software artifacts for a given product release. This paper highlights and discusses the development and deployment of an enterprise-level tool infrastructure that fits into the production build environment of a global automotive OEM. 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.
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