Title
Selection of Software Product Line Implementation Components Using Recommender Systems: An Application to Wordpress.
Abstract
In software products line (SPL), there may be features which can be implemented by different components, which means there are several implementations for the same feature. In this context, the selection of the best components set to implement a given configuration is a challenging task due to the high number of combinations and options which could be selected. In certain scenarios, it is possible to find information associated with the components which could help in this selection task, such as user ratings. In this paper, we introduce a component-based recommender system, called (REcommender System that suggests implementation Components from selecteD fEatures), which uses information associated with the implementation components to make recommendations in the domain of the SPL configuration. We also provide a RESDEC reference implementation that supports collaborative-based and content-based filtering algorithms to recommend (i.e., implementation components) regarding WordPress-based websites configuration. The empirical results, on a knowledge base with 680 plugins and 187 000 ratings by 116 000 users, show promising results. Concretely, this indicates that it is possible to guide the user throughout the implementation components selection with a margin of error smaller than 13% according to our evaluation.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2918469
IEEE ACCESS
Keywords
Field
DocType
Feature models,implementation components,recommender systems,software product line,wordpress
Recommender system,Software engineering,Computer science,Implementation,Reference implementation,Software,Software product line,Knowledge base,Plug-in,Margin of error,Distributed computing
Journal
Volume
ISSN
Citations 
7
2169-3536
1
PageRank 
References 
Authors
0.35
0
4
Name
Order
Citations
PageRank
Jorge Rodas-Silva110.35
Jose A. Galindo224821.10
Jorge Garcia-Gutierrez3359.33
David Benavides443630.52