Evaluating feature change impact on multi-product line configurations using partial information

Conference Paper (2014)
Author(s)

N.J.R. Dintzner (TU Delft - Software Engineering)

U. Kulesza (Federal University of Rio Grande do Norte)

A. van Deursen (TU Delft - Software Engineering)

M Pinzger (University of Klagenfurt)

Research Group
Software Engineering
Copyright
© 2014 N.J.R. Dintzner, U. Kulesza, A. van Deursen, M Pinzger
DOI related publication
https://doi.org/10.1007/978-3-319-14130-5_1
More Info
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Publication Year
2014
Language
English
Copyright
© 2014 N.J.R. Dintzner, U. Kulesza, A. van Deursen, M Pinzger
Research Group
Software Engineering
Bibliographical Note
Harvest@en
Pages (from-to)
1-16
ISBN (print)
978-3-319-14129-9
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Evolving large-scale, complex and highly variable systems is known to be a difficult task, where a single change can ripple through various parts of the system with potentially undesirable effects. In the case of product lines, and moreover multi-product lines, a change may affect only certain variants or certain combinations of features, making the evaluation of change effects more difficult.

In this paper, we present an approach for computing the impact of a feature change on the existing configurations of a multi-product line, using partial information regarding constraints between feature models. Our approach identifies the configurations that can no longer be derived in each individual feature model taking into account feature change impact propagation across feature models. We demonstrate our approach using an industrial problem and show that correct results can be obtained even with partial information. We also provide the tool we built for this purpose.

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