Configuration Prioritization for Variable Software Systems

Konfigurationsauswahl und -priorisierung mit QAOA

Karlsruhe Institute of Technology

The analyses of highly configurable systems yield hard problems due to the exponentially growing number of possible product configurations. This notebook demonstrates how to find configuartions for a feature model with attributed feature costs using a quantum computer. Found configurations should be valid and optimized regarding cost. To do this, in the notebook the Quantum Approximate Optimization Algorithm (QAOA) is used. The notebook first describes QAOA in different variants. Different implementations of the phase-separating operator which encodes the problem and the mixing operator are described. After that follows a description of how feature models can be transformed into an Ising model that can then be implemented as a quantum circuit and how to actually apply QAOA to the resulting Ising model. Finally, the scalability of the approach is briefly described.


The interactive demonstrator notebooks have been licensed under the Apache licence (version 2.0). The files may only be used in accordance with the licence. A copy of the licence can be downloaded from Except as required by applicable law or agreed to in writing, software distributed under this licence is distributed on an "AS IS" basis, without warranties or conditions of any kind, either express or implied. See the licence for the specific rights and restrictions associated with it.
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