Extending the automated feature model analysis capability of the abstract behavioral specification

Software Product Lines (SPL) support the concept of software mass production and customization by defining the commonalities and variability of related software products using a notion of features. The features of SPLs and their interdependencies are typically organized in feature models. These capture the product variations by defining permissible feature combinations. Analysis of feature models aims to extract valuable information and build a better software product line. The current implementation of automated analysis of feature models in Abstract Behavioral Specification (ABS) is using Choco Solver 2, a Java library for constraint satisfaction problems. Our work in this research was to port the implementation to the newest version of Choco Solver, namely Choco 4. Additionally, we extended the set of feature model analyses by adding new useful operations. An evaluation has been conducted to analyze the time performance. As a result, Choco 2 outperformed Choco 4 in case of deriving all solutions, while Choco 4 is better when deriving single solutions.