Vehicle's passengers and other traffic participants are protected more and more by integral safety systems. They continuously perceive the vehicle's environment to prevent dangerous situations by e.g. emergency braking systems. Furthermore, increasingly intelligent vehicle functions are still of major interest in research and development to reduce the risk of accidents. However, the development and testing of these functions should not rely only on validations on proving grounds and on long-term test-runs in real traffic; instead, they should be extended by virtual testing approaches to model potentially dangerous situations or to re-run specific traffic situations easily. This article outlines meta-metrics as one of today's challenges for the software engineering of these cyber-physical systems to provide guidance during the system development: For example, unstable results of simulation test-runs over the vehicle function's revision history are elaborated as an indicating metric where to focus on with real or further virtual test-runs; furthermore, varying acting time points for the same virtual traffic situation are indicating problems with the reliability to interpret the specific situation. In this article, several of such meta-metrics are discussed and assigned both to different phases during the series development and to different levels of detailedness of virtual testing approaches.