一句话：通过七个真实软件产品线的实证研究，探讨多目标进化搜索中保留无效解的影响，并给出保留有效解的经验指导。
多目标进化算法（MOEA）已成功用于软件产品线（SPL）搜索平衡多个目标的最优或近优解。然而，MOEA 常产生违反预定义约束的无效解，而无效解在实际中不可构建，因此是否在搜索过程中保留它们存在争议。论文在七个真实 SPL 上开展实验，其中包括当时报道的五个最大 SPL 以及两个具有真实质量属性取值与约束的 SPL，识别出保留无效解的三类潜在局限。基于当前最优方法，作者设计五种采用不同进化算子的算法变体，并通过性能评估给出关于如何保留有效解的经验指导。实证表明，是否保留无效解值得社区更多关注，且在某些情况下必须始终保留有效解。
Multi-objective evolutionary algorithms (MOEAs) have been successfully applied for software product lines (SPLs) to search for optimal or near-optimal solutions that balance multiple objectives. However, MOEAs usually produce invalid solutions that violate the constraints predefined. As invalid solutions are unbuildable in practice, we debate the preservation of invalid solutions during the search. We conduct experiments on seven real-world SPLs, including five largest SPLs hitherto reported and two SPLs with realistic values and constraints of quality attributes. We identify three potential limitations of preserving invalid solutions. Furthermore, based on the state-of-the-art, we design five algorithm variants that adopt different evolutionary operators. By performance evaluation, we provide empirical guidance on how to preserve valid solutions. Our empirical study demonstrates that whether or not to preserve invalid solutions deserves more attention in the community, and in some cases, we have to preserve valid solutions all along the way.
DOI 原文 ·
@inproceedings{paperbot4504,
title = {To preserve or not to preserve invalid solutions in search-based software engineering},
author = {Jianmei Guo and Kai Shi},
booktitle = {ICSE},
year = {2018},
doi = {10.1145/3180155.3180163}
}