Preference-based feature model configuration with multiple stakeholders

Feature model configuration is known to be a hard, error-prone and time-consuming activity. This activity gets even more complicated when it involves multiple stakeholders in the configuration process. Research work has proposed approaches to aid multi-stakeholder feature model configuration, but they rely on systematic processes that constraint decisions of some of the stakeholders. In this paper, we propose a novel approach to improve the multi-stakeholder configuration process, considering stakeholders' preferences expressed through both hard and soft constraints. Based on such preferences, we recommend different product configurations using different strategies from the social choice theory. We conducted an empirical study to evaluate the effectiveness of our strategies with respect to individual stakeholder satisfaction and fairness among all stakeholders. Results indicate that particular strategies perform best with respect to these aspects.