Scalable Product Line Configuration: A Straw to Break the Camel's Back

被引：0

作者：

Sayyad, Abdel Salam ^{[1
]}

Ingram, Joseph ^{[1
]}

Menzies, Tim ^{[1
]}

Ammar, Hany ^{[1
]}

机构：

[1] W Virginia Univ, Lane Dept Comp Sci & Elect Engn, Morgantown, WV 26506 USA

来源：

2013 28TH IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING (ASE) | 2013年

关键词：

Variability models; automated configuration; multiobjective optimization; evolutionary algorithms; SMT solvers; GENETIC ALGORITHM; SELECTION; PARETO;

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Software product lines are hard to configure. Techniques that work for medium sized product lines fail for much larger product lines such as the Linux kernel with 6000+ features. This paper presents simple heuristics that help the Indicator-Based Evolutionary Algorithm (IBEA) in finding sound and optimum configurations of very large variability models in the presence of competing objectives. We employ a combination of static and evolutionary learning of model structure, in addition to utilizing a pre-computed solution used as a "seed" in the midst of a randomly-generated initial population. The seed solution works like a single straw that is enough to break the camel's back -given that it is a feature-rich seed. We show promising results where we can find 30 sound solutions for configuring upward of 6000 features within 30 minutes.

引用

页码：465 / 474

页数：10

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