Group Recommendation Techniques for Feature Modeling and Configuration

TL;DR

This paper introduces group recommendation techniques to improve feature modeling and configuration processes in large-scale models, aiming to enhance stakeholder collaboration, satisfaction, and conflict resolution.

Contribution

It proposes novel group recommendation methods tailored for feature modeling and configuration, addressing navigation, satisfaction, and conflict issues in large-scale models.

Findings

Improved navigation support for feature models

Enhanced stakeholder satisfaction

Effective conflict resolution mechanisms

Abstract

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.