Options
MILPIBEA: Algorithm for Multi-objective Features Selection in (Evolving) Software Product Lines
Date Issued
2020-04-09
Date Available
2021-01-15T14:54:38Z
Abstract
Software Product Lines Engineering (SPLE) proposes techniques to model, create and improve groups of related software systems in a systematic way, with different alternatives formally expressed, e.g., as Feature Models. Selecting the 'best' software system(s) turns into a problem of improving the quality of selected subsets of software features (components) from feature models, or as it is widely known, Feature Configuration. When there are different independent dimensions to assess how good a software product is, the problem becomes even more challenging- it is then a multi-objective optimisation problem. Another big issue for software systems is evolution where software components change. This is common in the industry but, as far as we know, there is no algorithm designed to the particular case of multi-objective optimisation of evolving software product lines. In this paper we present MILPIBEA, a novel hybrid algorithm which combines the scalability of a genetic algorithm (IBEA) with the accuracy of a mixed-integer linear programming solver (IBM ILOG CPLEX). We also study the behaviour of our solution (MILPIBEA) in contrast with SATIBEA, a state-of-the-art algorithm in static software product lines. We demonstrate that MILPIBEA outperforms SATIBEA on average, especially for the most challenging problem instances, and that MILPIBEA is the one that continues to improve the quality of the solutions when SATIBEA stagnates (in the evolving context).
Sponsorship
Science Foundation Ireland
Type of Material
Book Chapter
Publisher
Springer International Publishing
Start Page
164
End Page
179
Series
Lecture Notes in Computer Science
12102
Copyright (Published Version)
2020 Springer Nature
Language
English
Status of Item
Peer reviewed
Part of
Paquete L., Zarges C. (eds.)., Evolutionary Computation in Combinatorial Optimization
ISBN
9783030436797
This item is made available under a Creative Commons License
File(s)
Owning collection
Scopus© citations
4
Acquisition Date
Mar 28, 2024
Mar 28, 2024
Views
602
Last Month
4
4
Acquisition Date
Mar 28, 2024
Mar 28, 2024
Downloads
350
Last Month
9
9
Acquisition Date
Mar 28, 2024
Mar 28, 2024