Kahn Process Networks (KPNs) are used for modeling streaming-oriented applications with changing behavior. To meet the performance and energy constraints of embedded devices, such applications must be mapped to parallel architectures in an optimal way. Finding an optimal mapping to the constrained architecture presumes that the behavior of the KPN is statically known. Considering the run-time behavior of streaming-oriented applications, we can identify run-time modes in which the system offers a certain behavior. In this book we present a static analysis that identifies such run-time modes at compile-time. The result is a mode automaton describing the whole network behavior. Optimizing backends that map KPNs to parallel architectures can be guided by these analysis results.