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SMTIBEA: a hybrid multi-objective optimization algorithm for configuring large constrained software product lines

  • Jianmei Guo*
  • , Jia Hui Liang
  • , Kai Shi
  • , Dingyu Yang
  • , Jingsong Zhang
  • , Krzysztof Czarnecki
  • , Vijay Ganesh
  • , Huiqun Yu
  • *此作品的通讯作者
  • East China University of Science and Technology
  • University of Waterloo
  • Shanghai Dianji University
  • CAS - Center for Excellence in Molecular Cell Science

科研成果: 期刊稿件 › 文章 › 同行评审

摘要

A key challenge to software product line engineering is to explore a huge space of various products and to find optimal or near-optimal solutions that satisfy all predefined constraints and balance multiple often competing objectives. To address this challenge, we propose a hybrid multi-objective optimization algorithm called SMTIBEA that combines the indicator-based evolutionary algorithm (IBEA) with the satisfiability modulo theories (SMT) solving. We evaluated the proposed algorithm on five large, constrained, real-world SPLs. Compared to the state-of-the-art, our approach significantly extends the expressiveness of constraints and simultaneously achieves a comparable performance. Furthermore, we investigate the performance influence of the SMT solving on two evolutionary operators of the IBEA.

源语言英语
页(从-至)1447-1466
页数20
期刊Software and Systems Modeling
卷18
期2
DOI
出版状态已出版 - 4 4月 2019
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