Paper Info
Title
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 < 0.01) for all five SPLs on all three quality indicators and with maximal effect size (Â12 = 1.0). We also present results that demonstrate the importance of combining constraint solving with search-based optimization and the significant improvement SATIBEA produces over pure constraint solving. Finally, we demonstrate the scalability of SATIBEA: within less than half an hour, it finds thousands of constraint-satisfying optimized software products, even for the largest SPL considered in the literature to date.
Year
DOI
Venue
2015
10.1109/ICSE.2015.69
ICSE
Keywords
Field
DocType
constraint solving,software product lines configuration,SPL feature selection,SATIBEA framework,multiobjective search-based optimization,diversity metrics
Systems engineering,Feature selection,Computer science,Cost estimate,Ranging,Software,Software product line,Frequency modulation,Genetic algorithm
Conference
Volume
ISSN
ISBN
1
0270-5257
978-1-4799-1934-5
Citations 
PageRank 
References 
58
1.08
39
Authors
4
Name
Order
Citations
PageRank
Christopher Henard138310.88
Mike Papadakis2111452.77
Mark Harman310264389.82
Yves Le Traon43922190.39