English

Consistency-based Merging of Variability Models

Artificial Intelligence 2021-02-16 v1

Abstract

Globally operating enterprises selling large and complex products and services often have to deal with situations where variability models are locally developed to take into account the requirements of local markets. For example, cars sold on the U.S. market are represented by variability models in some or many aspects different from European ones. In order to support global variability management processes, variability models and the underlying knowledge bases often need to be integrated. This is a challenging task since an integrated knowledge base should not produce results which are different from those produced by the individual knowledge bases. In this paper, we introduce an approach to variability model integration that is based on the concepts of contextual modeling and conflict detection. We present the underlying concepts and the results of a corresponding performance analysis.

Keywords

Cite

@article{arxiv.2102.07643,
  title  = {Consistency-based Merging of Variability Models},
  author = {Mathias Uta and Alexander Felfernig and Gottfried Schenner and Johannes Spoecklberger},
  journal= {arXiv preprint arXiv:2102.07643},
  year   = {2021}
}

Comments

M. Uta, A. Felfernig, G. Schenner, and J. Spoecklberger. Consistency-based Merging of Variability Models, Workshop on Configuration, pp. 9-12, Graz, Austria, 2018

R2 v1 2026-06-23T23:10:36.416Z