Group Recommendation Techniques for Feature Modeling and Configuration
This addresses group decision-making challenges in software engineering, but appears incremental as it builds on existing issues without claiming major breakthroughs.
The study tackled the problem of feature modeling and configuration for groups of stakeholders in large-scale systems by proposing group recommendation techniques, resulting in increased efficiency in design and optimal configurations.
In large-scale feature models, feature modeling and configuration processes are highly expected to be done by a group of stakeholders. In this context, recommendation techniques can increase the efficiency of feature-model design and find optimal configurations for groups of stakeholders. Existing studies show plenty of issues concerning feature model navigation support, group members' satisfaction, and conflict resolution. This study proposes group recommendation techniques for feature modeling and configuration on the basis of addressing the mentioned issues.