CPS are interconnected systems that observe and manipulate real objects and processes. They allow dynamic extension and show emergent behavior which leads to dynamic decision-making processes that can change at runtime. They cannot always be easily understood because of the high number of components involved. If an error occurs in such a process, it is difficult to comprehend which component involved in the decision process is responsible for that error. The decision therefore has a high degree of dependency on the nodes involved in the process. Therefore, errors are not easily traceable to their original source. In this paper, we present the idea of dependency trees, which should help to identify error sources in the event of a fault.