8 papers
Understanding Developer Pain Points in Federated Learning: Insights from Stack Overflow and GitHub
Sahand Saed, Khairul Alam, Banani Roy
Federated Learning (FL) enables collaborative model training without centralizing raw data, but building and operating FL systems remains difficult due to distributed execution, ra…
Maintenance and Support in Community-Driven Scientific Pipeline Ecosystems: A Cross-Platform Empirical Study of nf-core
Khairul Alam, Kowsik Roy, Md Shamimur Rahman +1
Community-driven scientific pipeline ecosystems are increasingly important for reproducible data-intensive research, but their sustainability depends on more than workflow engines,…
Analyzing GitHub Issues and Pull Requests in nf-core Pipelines: Insights into nf-core Pipeline Repositories
Khairul Alam, Banani Roy
Scientific Workflow Systems (SWSs) such as Nextflow have become essential software frameworks for conducting reproducible, scalable, and portable computational analyses in data-int…
Why Are AI Agent Involved Pull Requests (Fix-Related) Remain Unmerged? An Empirical Study
Khairul Alam, Saikat Mondal, Banani Roy
Autonomous coding agents (e.g., OpenAI Codex, Devin, GitHub Copilot) are increasingly used to generate fix-related pull requests (PRs) in real world software repositories. However,…
What Drives Issue Resolution Speed? An Empirical Study of Scientific Workflow Systems on GitHub
Khairul Alam, Banani Roy
Scientific Workflow Systems (SWSs) play a vital role in enabling reproducible, scalable, and automated scientific analysis. Like other open-source software, these systems depend on…
From Prompt to Pipeline: Large Language Models for Scientific Workflow Development in Bioinformatics
Khairul Alam, Banani Roy
Scientific Workflow Systems such as Galaxy and Nextflow are essential for scalable, reproducible, and automated bioinformatics analyses. However, developing and understanding scien…