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An Analysis of Variability Modeling Concepts: Expressiveness vs. Analyzability (Beitrag zu einer Tagung / Konferenz) - Einzelansicht

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Titel der Arbeit (title) An Analysis of Variability Modeling Concepts: Expressiveness vs. Analyzability
Erscheinungsjahr 2013
Verlag (publisher) Springer
Buchtitel (booktitle) Proceeding of the 13th International Conference on Software Reuse (ICSR '13)
Herausgeber_in (editor) John Favaro and Maurizio Morisio
Seitenzahl (pages) 32-48
Publikationsart Beitrag zu einer Tagung / Konferenz
Digital Object Identifier (DOI) 10.1007/978-3-642-38977-1_3
Abstract Variability modeling is a core activity of software product line engi-neering. Over the years, many different approaches to variability modeling have been proposed. Typically, the individual approaches have been designed with-out a detailed justification on why certain modeling concepts should be used. This yields a rather unfunded selection of modeling approaches in practice, e.g., selecting approaches that provide higher modeling concepts than actually need-ed, but less analyses capabilities than required. Thus, we propose that the focus of an analysis should not be to determine the best modeling language, but rather to provide a characterization on when to use what kind of approach. In particu-lar, the selection of one approach for a specific situation should be driven from the required modeling concepts (expressiveness) and the required analyzability. In this paper, we propose a classification of core concepts of variability model-ing based on expressiveness and analyzability. We discuss the methodology for and the classification of variability modeling concepts illustrated by a running example. The contribution of this paper is a modeling approach-independent classification of variability modeling concepts and their dependencies to pro-vide a systematic and rationale basis to anyone designing, standardizing, im-plementing or selecting a specific variability modeling approach.

Beteiligte Personen

Eichelberger, Holger, Dr.  
Kröher, Christian  M.Sc.  
Schmid, Klaus, Professor Dr. rer. nat.  


Abt. Software Systems Engineering


Projekt Indenica
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