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Mining complex feature correlations from software product line configurations

 
: Zhang, Bo; Becker, Martin

:

Gnesi, S. ; Association for Computing Machinery -ACM-:
Seventh International Workshop on Variability Modelling of Software-intensive Systems, VaMoS 2013. Proceedings : Pisa, Italy, January 23 - 25, 2013
New York: ACM, 2013
ISBN: 978-1-4503-1541-8
Art. 19, 7 S.
International Workshop on Variability Modelling of Software-Intensive Systems (VaMoS) <7, 2013, Pisa>
Englisch
Konferenzbeitrag
Fraunhofer IESE ()

Abstract
As a Software Product Line (SPL) evolves with increasing number of features and feature values, the feature correlations become extremely intricate, and the specifications of these correlations tend to be either incomplete or inconsistent with their realizations, causing misconfigurations in practice. In order to guide product configuration processes, we present a solution framework to recover complex feature correlations from existing product configurations. These correlations are further pruned automatically and validated by domain experts. During implementation, we use association mining techniques to automatically extract strong association rules as potential feature correlations. This approach is evaluated using a large-scale industrial SPL in the embedded system domain, and finally we identify a large number of complex feature correlations.

: http://publica.fraunhofer.de/dokumente/N-234659.html