Leveraging belief uncertainty for informed decision making in software product line evolution

Software Product Lines (SPL) are not static software artifacts, but they evolve over time. The planning, realization, and release of a SPL requires many high-level decisions involving many different stakeholders with different expertise. Taking their opinions into account to make the right decisions is not trivial. Currently there are no mechanisms to assist stakeholders in the decision making process in an informed manner. In this paper, we propose the use of belief uncertainty in conjunction with feature models to assist in the evolution of SPLs by explicitly quantifying opinions and their associated uncertainty. We present a novel approach in which subjective logic is used to represent the opinions of stakeholders in three evolution scenarios, namely feature model evolution, next release problem and variability reduction. We apply our approach to the evolution of the Xiaomi MiBand SmartWatch SPL over the time period from July 2014 to October 2023. We present an implementation of our approach and evaluate its scalability. • Novel approach for decision making during SPL evolution. • Applicable to different evolution scenarios: feature planning, next release problem and variability reduction. • Use of subjective logic to quantify stakeholder beliefs (opinions). • Illustration on the evolution of a real-world SPL – the Xiaomi MiBand SPL – from July 2014 to October 2023. • Proof of concept implementation in Python.