Year: 2025
Type: conference-paper
Abstract: Uniform random sampling (URS) has many applications in configurable systems analysis.Usually, feature models consisting of a hierarchical feature diagram and additional side constraints specify the space of valid configurations to be sampled from.However, URS has predominately been applied on feature models translated a priori into conjunctive normal form (CNF).In this work, we study URS approaches that instead operate directly on feature diagrams and provide a comparative evaluation of their performance against well-established URS tools for CNF representations.Our findings suggest that translating feature models to CNF offers advantages, even in the presence of only few side constraints.
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4410812101
