Visualizations for the evolution of Variant-Rich Systems: A systematic mapping study: A systematic mapping study

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2023-02
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Context: Variant-Rich Systems (VRSs), such as Software Product Lines or variants created through clone & own, aim at reusing existing assets. The long lifespan of families of variants, and the scale of both the code base and the workforce make VRS maintenance and evolution a challenge. Visualization tools are a needed companion. Objective: We aim at mapping the current state of visualization interventions in the area of VRS evolution. We tackle evolution in both functionality and architecture. Three research questions are posed: What sort of analysis is being conducted to assess VRS evolution? (Analysis perspective); What sort of visualizations are displayed? (Visualization perspective); What is the research maturity of the reported interventions? (Maturity perspective). Methods: We performed a systematic mapping study including automated search in digital libraries, expert knowledge, and snowballing. Results: The study reports on 41 visualization approaches to cope with VRS evolution. Analysis wise, feature identification and location is the most popular scenario, followed by variant integration towards a Software Product Line. As for visualization, nodelink diagram visualization is predominant while researchers have come up with a wealth of ingenious visualization approaches. Finally, maturity wise, almost half of the studies are solution proposals. Most of the studies provide proof-of-concept, some of them also include publicly available tools, yet very few face proof-of-value. Conclusions: This study introduces a comparison framework where to frame future studies. It also points out distinct research gaps worth investigating as well as shortcomings in the evidence about relevance and contextual considerations (e.g., scalability).
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Publisher Copyright: © 2022 The Author(s)
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Medeiros , R , Martinez , J , Díaz , O & Falleri , J-R 2023 , ' Visualizations for the evolution of Variant-Rich Systems: A systematic mapping study : A systematic mapping study ' , Information and Software Technology , vol. 154 , 107084 , pp. 107084 . https://doi.org/10.1016/j.infsof.2022.107084