Dynamische Rekonfigurationsmethodik für zuverlässige, echtzeitfähige Eingebettete Systeme in Automotive

Currently, dynamically reconfigurable systems are not used in automotive and there is no process model for their development. The focus of this dissertation is to explore methods and approaches for the development of such systems. One major architectural driver is autonomous driving, another is functional high integration on central computing platforms. Taking these into account, dynamic reconfiguration is classified and explored

XANDAR: X-by-Construction Design framework for Engineering Autonomous & Distributed Real-time Embedded Software Systems

The next generation of networked embedded systems (ES) necessitates rapid prototyping and high performance while maintaining key qualities like trustworthiness and safety. However, development of safety-critical ES suffers from complex software (SW) toolchains and engineering processes. Moreover, the current trend in autonomous systems, which relies on Machine Learning (ML) and AI applications when combined with fail-operational requirements renders the Verification and Validation (V&V) of these new systems a challenging endeavor. Prime examples are Advanced Driver-Assistance Systems (ADAS) that are prone to various safety/security vulnerabilities. The XANDAR project aims at developing a mature SW toolchain (from requirements analysis to the actual code integration on target including V&V) fulfilling the needs of industry for rapid prototyping of interoperable and autonomous ES. Starting from a model-based system architecture, XANDAR will leverage automatic model synthesis and software parallelization techniques to achieve specific non-functional requirements setting the foundation for a novel (real-time, safety-, and security)-by-Construction paradigm