Paper Info
Title
Is seeding a good strategy in multi-objective feature selection when feature models evolve?
Abstract
Context: When software architects or engineers are given a list of all the features and their interactions (i.e., a Feature Model or FM) together with stakeholders’ preferences – their task is to find a set of potential products to suggest the decision makers. Software Product Lines Engineering (SPLE) consists in optimising those large and highly constrained search spaces according to multiple objectives reflecting the preference of the different stakeholders. SPLE is known to be extremely skill- and labour-intensive and it has been a popular topic of research in the past years.
Year
DOI
Venue
2018
10.1016/j.infsof.2017.08.010
Information and Software Technology
Keywords
Field
DocType
Software product lines,Multi-objective,Genetic algorithm,Evolution
Data mining,Feature selection,Industrial engineering,Computer science,Software system,Software,Feature model,Execution time,Database,Genetic algorithm,Seeding
Journal
Volume
ISSN
Citations 
95
0950-5849
6
PageRank 
References 
Authors
0.43
46
4
Name
Order
Citations
PageRank
Takfarinas Saber161.10
David Brevet260.43
Goetz Botterweck362046.72
Anthony Ventresque410817.08