Taming and optimizing feature interaction in software-intensive automotive systems
Sven Dominka, Dominik Ertl, Michael Dübner, Romana Wiesinger, Hermann Kaindl · 2018
The number of cyber-physical features within automotive systems rises significantly. Features are often not independent from each other, i.e., they interact. Such interaction is either known and desired or unknown and undesired. We propose a holistic approach consisting of four different quality assurance measures to tame undesired and optimize desired interaction: A generic feature framework, a central feature coordinator, an analytical measure based on coupling metrics and a dynamic feature testing approach. In this paper, we present these four measures as well as their implementation and evaluation.