On the value of user preferences in search-based software engineering: A case study in software product lines

Software design is a process of trading off competing objectives. If the user objective space is rich, then we should use optimizers that can fully exploit that richness. For example, this study configures software product lines (expressed as feature maps) using various search-based software enginee...

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Bibliographic Details
Published in2013 35th International Conference on Software Engineering (ICSE) pp. 492 - 501
Main Authors Sayyad, Abdel Salam, Menzies, Tim, Ammar, Hany
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2013
Subjects
Evolutionary computation
Feature Models
Indicator-Based Evolutionary Algorithm
Mobile handsets
Multiobjective Optimization
Optimal Feature Selection
Optimization
Search-Based Software Engineering
Sociology
Software
Software algorithms
Software engineering
Software Product Lines
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ISBN9781467330732
1467330736
ISSN0270-5257
DOI10.1109/ICSE.2013.6606595

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Summary:Software design is a process of trading off competing objectives. If the user objective space is rich, then we should use optimizers that can fully exploit that richness. For example, this study configures software product lines (expressed as feature maps) using various search-based software engineering methods. As we increase the number of optimization objectives, we find that methods in widespread use (e.g. NSGA-II, SPEA2) perform much worse than IBEA (Indicator-Based Evolutionary Algorithm). IBEA works best since it makes most use of user preference knowledge. Hence it does better on the standard measures (hypervolume and spread) but it also generates far more products with 0% violations of domain constraints. Our conclusion is that we need to change our methods for search-based software engineering, particularly when studying complex decision spaces.
ISBN:9781467330732
1467330736
ISSN:0270-5257
DOI:10.1109/ICSE.2013.6606595