Towards Cloud-supported Automotive Software Development and Test

The development of automotive software has been an evolving process for the last decades. As a result, the paradigm of software development which is independent of the target hardware platform has been adopted in almost all parts of the automotive industry. Deploying software to a hardware platform is now controlled by an enormous parameter set stored in a mapping configuration. This led to the creation of numerous vendor-specific tools for electronic control unit (ECU) development. While this approach simplifies and supports the re-usability of vehicle functions it also increases the complexity as well as the difficulty for integration tests and error localization. In this paper, we present a conceptual platform which allows to establish references between different development and test phase items in a developer-friendly way. It revolves around two self-developed tools supported by an extensive AUTOSAR knowledge base. The system creates inter-connectivity so that it becomes easier to locate the actual origin of a misbehavior or to find a test error manifestation in the actual end system for developers and testers alike.

ERROR LOCALIZATION DIAGNOSTIC MODEL OPTIMIZATION IN DIGITAL STATE MACHINES NETWORKS

The problem of constructing a diagnostic model for a network S consisting of a number of digital automata is considered, provided that the diagnostic models of all network components are known. It is assumed that these models are given by systems of logical equations, and the errors to be detected are localized in any but a single component of the network.