Paper Info
Title
Grammar Based Genetic Programming for Software Configuration Problem.
Abstract
Software Product Lines (SPLs) capture commonalities and variability of product families, typically represented by means of feature models. The selection of a set of suitable features when a software product is configured is typically made by exploring the space of treadoffs along different attributes of interest, for instance cost and value. In this paper, we present an approach for optimal product configuration by exploiting feature models and grammar guided genetic programming. In particular, we propose a novel encoding of candidate solutions, based on grammar representation of feature models, which ensures that relations imposed in the feature model are respected by the candidate solutions.
Year
DOI
Venue
2017
10.1007/978-3-319-66299-2_10
Lecture Notes in Computer Science
Keywords
Field
DocType
Genetic programming,Grammar,Feature model,Software product line
Programming language,Programming paradigm,Computer science,Inductive programming,Adaptive grammar,Feature model,Software product line,Software construction,Software development,Software framework
Conference
Volume
ISSN
Citations 
10452
0302-9743
2
PageRank 
References 
Authors
0.38
8
6
Name
Order
Citations
PageRank
Fitsum Meshesha Kifetew115714.92
Denisse Muñante220.72
Jesús Gorroñogoitia3223.66
Alberto Siena429727.63
Angelo Susi5105783.69
Anna Perini6120070.76