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Mining Complex Feature Correlations from Large Software Product Line Configurations

  • 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.

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Metadaten
Author:Bo Zhang
URN (permanent link):urn:nbn:de:hbz:386-kluedo-35013
Document Type:Preprint
Language of publication:English
Publication Date:2013/03/04
Year of Publication:2013
Publishing Institute:Technische Universität Kaiserslautern
Date of the Publication (Server):2013/05/07
Number of page:8
Faculties / Organisational entities:Fachbereich Informatik
CCS-Classification (computer science):D. Software
DDC-Cassification:0 Allgemeines, Informatik, Informationswissenschaft / 004 Informatik
Licence (German):Standard gemäß KLUEDO-Leitlinien vom 10.09.2012