Combining Multi-Objective Search and Constraint Solving for Configuring Large Software Product Lines
Abstract
Software Product Line (SPL) feature selection involves the optimization of multiple objectives in a large and highly constrained search space. We introduce SATIBEA, that augments multi-objective search-based optimization with constraint solving to address this problem, evaluating it on five large real-world SPLs, ranging from 1,244 to 6,888 features with respect to three different solution quality indicators and two diversity metrics. The results indicate that SATIBEA statistically significantly outperforms the current state-of-the-art (p
BibTeX
@inproceedings{Henard-al:ICSE15,
author = {Christopher Henard and
Mike Papadakis and
Mark Harman and
Yves Le Traon},
title = {Combining {Multi-Objective} Search and Constraint Solving for Configuring Large Software Product Lines},
booktitle = {ICSE (Part I)},
pages = {517--528},
publisher = {{IEEE} Computer Society},
year = {2015},
}