* ICSE 2018 *
Sun 27 May - Sun 3 June 2018 Gothenburg, Sweden
Fri 1 Jun 2018 14:20 - 14:40 at J1 room - Search-Based Software Engineering II Chair(s): Daniel Varro

The optimal feature selection problem in software product line is typically addressed by the approaches based on Indicator-based Evolutionary Algorithm (IBEA). In this study, we first expose the mathematical nature of this problem — multi-objective binary integer linear programming. Then, we implement/propose three mathematical programming approaches to solve this problem at different scales. For small-scale problems (roughly, less than 100 features), we implement two established approaches to find all exact solutions. For medium-to-large problems (roughly, more than 100 features), we propose one efficient approach that can generate a representation of the entire Pareto front in linear time complexity. The empirical results show that our proposed method can find significantly more non-dominated solutions in similar or less execution time, in comparison with IBEA and its recent enhancement (i.e., IBED that combines IBEA and Differential Evolution).

Fri 1 Jun

icse-2018-Technical-Papers
14:00 - 15:30: Technical Papers - Search-Based Software Engineering II at J1 room
Chair(s): Daniel Varro
icse-2018-Technical-Papers152785440000014:00 - 14:20
Talk
DOI Pre-print Media Attached
icse-2018-Technical-Papers152785560000014:20 - 14:40
Talk
DOI Pre-print Media Attached
icse-2018-Journal-first-papers152785680000014:40 - 15:00
Talk
icse-2018-Technical-Papers152785800000015:00 - 15:20
Talk
Pre-print
icse-2018-Technical-Papers152785920000015:20 - 15:30
Talk