The complexity of automotive applications is continuously increasing, leading to a growing demand for methodologies that offer comprehensive mixed-signal verification. However, compared to the highly automated verification methodologies in the digital domain, pre-silicon verification in the analog domain still implies a substantial amount of manual work and computational effort. Apart from this, automotive applications most often have to comply with functional safety standards and therefore their robustness concerning safety-critical faults needs to be proven. This is normally ensured by performing safety verification with faults being purposefully injected into the designs. In this paper we present a methodology that enables a regression-based mixed-signal verification combined with an existing approach for analog safety analysis. Both concepts are applied to an automotive design, in which faults have been injected, in order to demonstrate their capabilities.     «

The complexity of automotive applications is continuously increasing, leading to a growing demand for methodologies that offer comprehensive mixed-signal verification. However, compared to the highly automated verification methodologies in the digital domain, pre-silicon verification in the analog domain still implies a substantial amount of manual work and computational effort. Apart from this, automotive applications most often have to comply with functional safety standards and therefore thei...     »