A 3D visualization approach mapping topics found across a project's socio-technical artifacts onto vegetation-covered islands, where the individual artifacts are depicted as trees of various types.
Abstract
Projects hosted on collaborative software development platforms, such as GitHub, include many non-code artifacts documenting the project's lifecycle, with its challenges, plans, design, and even community. These socio-technical artifacts include, for example, bug reports, feature requests, and forum posts, offering a useful prospect on the project's evolution. However, these artifacts are dispersed over multiple communication channels and written in natural language, making their analysis difficult, as they are fragmented and with considerable noise. We present a 3D visualization approach mapping topics found across a project's socio-technical artifacts onto vegetation-covered islands, where the individual artifacts are depicted as trees of various types. The topic islands rise out of the ocean as they become discussed, to sink again when they are no longer so. We built a prototype implementing the entire visualization pipeline, from data mining to interactive rendering, leveraging machine learning techniques to cluster the artifacts and extract their topics. We present, through several case studies, the insights that our approach elicits about discussions of development topics throughout a project's history. The user study we conducted (N=34) further strengthens our conclusions about its suitability for understanding socio-technical artifacts and their evolution.
Ritgard is presented, a tool that mines GitHub repositories for their STAs, namely Issues, Pull Requests, and Discussions, and visualizes them as 3D islands covered with trees, depicting the evolution of features and concerns throughout the project's lifetime.
Adam J. Stepánek, Marco Raglianti, J. Byška et al.· 0 citations
A longitudinal analysis of generative-AI-related discussions in the Visual Studio Code (VS Code) GitHub repository, using 43,806 candidate issues created between January 2021 and June 2026, suggests that GitHub Issues provide a practical, workflow-oriented perspective on generative AI that complements survey-based stud...
Panida Rumriankit, Akito Monden, Hiroki Inayoshi et al.· 0 citations
User Stories are key artifacts in Requirement and Software Engineering. Despite their wide adoption, their writing in industrial contexts tends to diverge from the principles initially stated in Agile methodologies. In this context, sets of metrics such as INVEST or QUS emerged to qualify these items. In this paper, we...
M. Ortega, Hassan Imhah, N. Mellouli et al.· Proceedings of the ACM on So...· 0 citations
A large-scale empirical study of Galaxy describes Galaxy maintenance as a distributed ecosystem-level process and identifies opportunities to improve diagnostic reporting, lifecycle-aware triage, cross-space traceability, and the reuse of community-support knowledge.
As software usage continues to expand, package managers automatically resolve dependencies to construct a dependency graph based on user-specified requirements. These explicitly declared dependencies, known as direct dependencies, receive significant attention in terms of maintainability and security. However, implicit...
Lyuye Zhang, Chengwei Liu, Fang-Yuan Zhang et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.