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Comparison of exact and approximate multi-objective optimization for software product lines

Published:15 September 2014Publication History

ABSTRACT

Software product lines (SPLs) allow stakeholders to manage product variants in a systematical way and derive variants by selecting features. Finding a desirable variant is often difficult, due to the huge configuration space and usually conflicting objectives (e.g., lower cost and higher performance). This scenario can be characterized as a multi-objective optimization problem applied to SPLs. We address the problem using an exact and an approximate algorithm and compare their accuracy, time consumption, scalability, parameter setting requirements on five case studies with increasing complexity. Our empirical results show that (1) it is feasible to use exact techniques for small SPL multi-objective optimization problems, and (2) approximate methods can be used for large problems but require substantial effort to find the best parameter setting for acceptable approximation which can be ameliorated with known good parameter ranges. Finally, we discuss the tradeoff between accuracy and time consumption when using exact and approximate techniques for SPL multi-objective optimization and guide stakeholders to choose one or the other in practice.

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      • Published in

        cover image ACM Other conferences
        SPLC '14: Proceedings of the 18th International Software Product Line Conference - Volume 1
        September 2014
        377 pages
        ISBN:9781450327404
        DOI:10.1145/2648511

        Copyright © 2014 ACM

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        Publication History

        • Published: 15 September 2014

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        SPLC '14 Paper Acceptance Rate36of97submissions,37%Overall Acceptance Rate167of463submissions,36%

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