Abstract

Feature models (FMs) appeared more than 30 years ago, and they are valuable tools for modeling the functional variability of systems. The automated analysis of feature models (AAFM) is currently a thriving, motivating, and active research area. The product configuration of FMs is a relevant and helpful operation, a crucial activity overall with large-scale feature models. The minimal conflict detection, the diagnosis of in-conflict configuration, and the product completion of consistent partial configuration are significant operations for obtaining consistent and well-defined products. Overall, configuring products for large-scale variability intensive systems (VIS) asks for efficient automated solutions for minimal conflict, diagnosis, and product configuration. Given the relevance of minimal conflict, diagnosis, and product configuration, and the current application of large-scale configuration and FMs for representing those systems and products, the main goals of this research paper are to establish the fundaments of the product configuration of feature models and systematically review existing solutions for the conflict detection, diagnosis, and product completion in FMs from 2010 to 2019. We can perceive that even though modern computing approaches exist for AAFM operations, no solutions exist for assisting the product configurations before 2020. This article reports that in 2020, new solutions appear regarding applying parallel computing for those goals. This research highlights research opportunities for developing new and more efficient solutions for conflict detection, diagnosis, and product completion of large-scale configurations.