by Wesley K. G. Assunção, Roberto E. Lopez-Herrejon, Lukas Linsbauer, Silvia R. Vergilio, Alexander Egyed
Abstract:
To effectively cope with increasing customization demands, companies that have developed variants of software systems are faced with the challenge of consolidating all the variants into a Software Product Line, a proven development paradigm capable of handling such demands. A crucial step in this challenge is to reverse engineer feature models that capture all the required feature combinations of each system variant. Current research has explored this task using propositional logic, natural language, and search-based techniques. However, using knowledge from the implementation artifacts for the reverse engineering task has not been studied. We propose a multi-objective approach that not only uses standard precision and recall metrics for the combinations of features but that also considers variability-safety, i.e. the property that, based on structural dependencies among elements of implementation artifacts, asserts whether all feature combinations of a feature model are in fact well-formed software systems. We evaluate our approach with five case studies and highlight its benefits for the software engineer.
Reference:
Extracting Variability-Safe Feature Models from Source Code Dependencies in System Variants (Wesley K. G. Assunção, Roberto E. Lopez-Herrejon, Lukas Linsbauer, Silvia R. Vergilio, Alexander Egyed), In Proceedings of the Genetic and Evolutionary Computation Conference, (GECCO 2015), Madrid, Spain, 2015.
Bibtex Entry:
@Conference{DBLP:conf/gecco/AssuncaoLLVE15,
author = {Assunção, Wesley K. G. and Roberto E. Lopez{-}Herrejon and Lukas Linsbauer and Silvia R. Vergilio and Alexander Egyed},
title = {Extracting Variability-Safe Feature Models from Source Code Dependencies in System Variants},
booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference, (GECCO 2015), Madrid, Spain},
year = {2015},
pages = {1303--1310},
abstract = {To effectively cope with increasing customization demands, companies
that have developed variants of software systems are faced with the
challenge of consolidating all the variants into a Software Product
Line, a proven development paradigm capable of handling such demands.
A crucial step in this challenge is to reverse engineer feature models
that capture all the required feature combinations of each system
variant. Current research has explored this task using propositional
logic, natural language, and search-based techniques. However, using
knowledge from the implementation artifacts for the reverse engineering
task has not been studied. We propose a multi-objective approach
that not only uses standard precision and recall metrics for the
combinations of features but that also considers variability-safety,
i.e. the property that, based on structural dependencies among elements
of implementation artifacts, asserts whether all feature combinations
of a feature model are in fact well-formed software systems. We evaluate
our approach with five case studies and highlight its benefits for
the software engineer.},
bibsource = {dblp computer science bibliography, http://dblp.org},
biburl = {http://dblp.uni-trier.de/rec/bib/conf/gecco/AssuncaoLLVE15},
doi = {10.1145/2739480.2754720},
file = {:Conferences\\GECCO 2015 - Extracting Variability-Safe Feature Models from Source Code Dependencies in System Variants\\Extracting Variability-Safe Feature Models from Source Code Dependencies in System Variants-preprint.pdf:PDF},
keywords = {FWF P25289},
timestamp = {Wed, 30 Dec 2015 09:05:01 +0100},
url = {http://doi.acm.org/10.1145/2739480.2754720},
}