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Automotive systems are safety-critical cyber-physical systems. In particular, undesired feature interaction can lead to safety-critical behavior. In order to address this problem, we investigate physical feature interaction in this context using simulation (with more than one physical variable). This allows us to visualize both the behavior of features in isolation and their interaction. Our major result is a new insight about feature coordination. In such a cyberphysical context, it can be insufficient to coordinate as usual by giving one feature priority over another one. Instead, coordinating based on a physical variable involved in the feature interaction appears to be both necessary and sufficient. In summary, we present our investigation of safetycritical feature interactions and their coordination in automotive systems using simulation, and its results.

Embedded systems include an increasing share of analog/mixed-signal components that are tightly interwoven with functionality of digital HW/SW systems. A challenge for verification is that even small deviations in analog components can lead to significant changes in system properties. In this paper we propose the combination of range-based, semisymbolic simulation with assertion checking. We show that this approach combines advantages, but as well some limitations, of multirun simulations with formal techniques. The efficiency of the proposed method is demonstrated by several examples.

Ahstract-This work addresses the increasing danger of ship ping integrated circuits (either fully digital or mixed signal) that contain malicious hardware modifications. Potential security threads are established by so called hardware Trojans, imple mented in the physical silicon structure. A desire of system engineers is to identify such back-door functionalities during an early design phase. The paper discusses how techniques deduced from model checking applications can be used for Trojan detection. A set of potential malicious properties is defined and handed to an automatic tool. Any returned counterexample identifies a feasible attack path and is a basis for further detailed inspection. *