Consistency-based integration of multi-stakeholder recommender systems with feature model configuration

Abstract

Feature models are used to represent variability properties of complex items. In most of the cases, the assumption in feature model configuration is that single users/stakeholders are interacting with the underlying configurator. However, there are many scenarios where multiple stakeholders need to jointly complete a configuration task, for example, when selecting the features to be included in a company-wide software service or when deciding about the software features to be included in upcoming releases. In such cases, decisions have to be taken jointly where the constraints and preferences of individual stakeholders have to be taken into account. In this paper, we show how multi-stakeholder recommender systems can be integrated in feature model configuration scenarios.