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

Abstract

Variant-Rich Systems (VRSs), such as Software Product Lines or variants created through clone & own, are created to satisfy different needs while reusing existing assets. The long lifespan of families of variants, and the scale of both the technical side (implementation size) and the organizational side (roles diversity) make their maintenance and evolution a challenge. Visualization tools are a needed companion. We aim at mapping the current state of visualization interventions in the area of VRS evolution. We tackle evolution in both the functionality and the variability management architecture. Three research questions are posed: What sort of analysis is being conducted? (Analysis perspective); What sort of visualizations are displayed? (Visualization perspective); What types of research have been reported and how have they been evaluated? (Maturity perspective). We performed a systematic mapping study including automated search in digital libraries, expert knowledge, and snowballing. 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-concepts, some of them also include public available tools, yet very few face proof-of-value. This systematic mapping 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). • Variants-rich systems evolution is a challenge task. • We conducted a SMS over 41 primary sources targeting Variant-Rich system evolution visualization. • The area is sustainably covered and diverse in terms of visualization and tools. • The results show a lack of formal evaluations in industrial settings. • The area lacks scalability awareness. • Some evolution scenarios are overlooked.