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  3. A conceptual model for unifying variability in space and time: Rationale, validation, and illustrative applications

A conceptual model for unifying variability in space and time: Rationale, validation, and illustrative applications

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DOI
10.48620/88799
Publisher DOI
10.1007/s10664-021-10097-z
Abstract
With the increasing demand for customized systems and rapidly evolving technology, software engineering faces many challenges. A particular challenge is the development and maintenance of systems that are highly variable both in space (concurrent variations of the system at one point in time) and time (sequential variations of the system, due to its evolution). Recent research aims to address this challenge by managing variability in space and time simultaneously. However, this research originates from two different areas, software product line engineering and software configuration management, resulting in non-uniform terminologies and a varying understanding of concepts. These problems hamper the communication and understanding of involved concepts, as well as the development of techniques that unify variability in space and time. To tackle these problems, we performed an iterative, expert-driven analysis of existing tools from both research areas to derive a conceptual model that integrates and unifies concepts of both dimensions of variability. In this article, we first explain the construction process and present the resulting conceptual model. We validate the model and discuss its coverage and granularity with respect to established concepts of variability in space and time. Furthermore, we perform a formal concept analysis to discuss the commonalities and differences among the tools we considered. Finally, we show illustrative applications to explain how the conceptual model can be used in practice to derive conforming tools. The conceptual model unifies concepts and relations used in software product line engineering and software configuration management, provides a unified terminology and common ground for researchers and developers for comparing their works, clarifies communication, and prevents redundant developments.
Date Issued
2022-05-30
Publication Type
Article
Language(s)
en
Author(s)
Ananieva, Sofia
Greiner, Sandra
Kehrer, Timo  orcid-logo
Institute of Computer Science, Software Engineering Group (SEG)  
Institute of Computer Science  
Krüger, Jacob
Kühn, Thomas
Linsbauer, Lukas
Grüner, Sten
Koziolek, Anne
Lönn, Henrik
Ramesh, S.
Reussner, Ralf
Additional Credits
Institute of Computer Science  
Institute of Computer Science, Software Engineering Group (SEG)  
Journal
Empirical Software Engineering
Publisher
Springer
ISSN
1382-3256
1573-7616
Access(Rights)
open.access
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