Seifermann, StephanWerle, DominikEbada, MazenKelter, Udo2023-02-272023-02-272019https://dl.gi.de/handle/20.500.12116/40485Predicting quality properties such as privacy are reasonable use cases for Data Flow Models (DFMs). For other use cases such as performance prediction, component-based software architecture models focusing on control flows are more suitable. Designers can derive a Control Flow Model (CFM) from a DFM but they have to make numerous design decisions like defining operation signatures. Currently, this derivation is a creative process without a clear design space and without guidelines for navigating this space. In this paper, we present design alternatives for given data flow examples and derive mapping rules that allow to choose between reasonable alternatives. Our results are a first step towards a catalogue of rules for deriving CFMs from DFMs in a systematic way and providing semi-automated transformations.enperformancepredictionData Flow ModelControl Flow ModeltransformationText/Conference Paper0720-8928