Galaxy maintenance spans tools workflows and user support challenges
Understanding Maintenance and Support in a Community-Driven Scientific Workflow Ecosystem: A Cross-Space Study of Galaxy
Software Engineering
Summary
Maintaining a popular scientific software called Galaxy requires work across many areas like code, user tools, workflows, and help forums. The authors studied over 70,000 related documents from GitHub and community forums to understand what kind of maintenance is done and how issues get fixed. They found that most problem-solving happens inside developer spaces, with little connection to user support discussions. This shows Galaxy maintenance is spread out across different places and highlights ways to improve how issues are tracked and handled across these spaces.
What this means in practice
- •For open source project managers: Improve coordination and issue tracking by integrating development and support discussions in large community-driven projects like Galaxy.
- •For scientific software engineers: Design lifecycle-aware tools that better identify and triage maintenance concerns across code repositories and user forums.
Authors
Khairul Alam, Kowsik Roy, Md Shamimur Rahman, Banani Roy
Abstract
Galaxy is a widely used, community-driven scientific workflow system whose sustainability depends on continuous maintenance across its software, tools, workflows, infrastructure, documentation, and user-support ecosystem. However, maintenance knowledge in Galaxy is distributed across development and community-support spaces, making it difficult to understand what is maintained, how maintenance artifacts are resolved, and how user-facing concerns connect to repository-level development. We conduct a large-scale empirical study of Galaxy using 11,762 GitHub issues, 52,203 pull requests, and 6,235 Community Forum discussions. We characterize maintenance and support concerns, examine factors associated with resolution outcomes and resolution time, and investigate explicit and candidate connections among maintenance artifacts across these spaces. Using BERTopic modeling, we identify nine issue topics, 14 pull-request topics, and 14 forum topics, revealing a maintenance landscape spanning workflow execution, data management, tools and dependencies, infrastructure, testing, scientific resources, documentation, and user support. Resolution analyses show that coordination, diagnostic, contributor, automation, and engagement characteristics exhibit different associations with whether artifacts are resolved and how quickly resolution occurs. We further find limited explicit traceability between development and support spaces: 97.77\% of 16,426 resolved explicit relationships occur within GitHub, while only 294 connect GitHub artifacts with Community Forum discussions, despite additional semantic and technical relatedness across these spaces. Together, these findings characterize Galaxy maintenance as a distributed ecosystem-level process and identify opportunities to improve diagnostic reporting, lifecycle-aware triage, cross-space traceability, and the reuse of community-support knowledge.