8 papers · 1 filter
"Go Home Copilot, You're Drunk": Understanding Developer Responses to Agent-Generated Code Review Comments
Shamse Tasnim Cynthia, Ratnadira Widyasari, Banani Roy +2
Code review is a critical quality assurance practice in software engineering development, and AI coding agents are increasingly generating review comments on pull requests. However…
From Generic to Personalized: Exploring Persona-Aware Code Review Explanations
Shamse Tasnim Cynthia, Ratnadira Widyasari, Banani Roy +2
Code review is essential for ensuring software quality and supporting collaboration, yet prior work shows that developers can interpret code review comments differently. These diff…
Beyond Bug Fixes: An Empirical Investigation of Post-Merge Code Quality Issues in Agent-Generated Pull Requests
Shamse Tasnim Cynthia, Al Muttakin, Banani Roy
The increasing adoption of AI coding agents has increased the number of agent-generated pull requests (PRs) merged with little or no human intervention. Although such PRs promise p…
Are We All Using Agents the Same Way? An Empirical Study of Core and Peripheral Developers Use of Coding Agents
Shamse Tasnim Cynthia, Joy Krishan Das, Banani Roy
Autonomous AI agents are transforming software development and redefining how developers collaborate with AI. Prior research shows that the adoption and use of AI-powered tools dif…
Towards LLM-Powered Task-Aware Retrieval of Scientific Workflows for Galaxy
Shamse Tasnim Cynthia, Banani Roy
Scientific Workflow Management Systems (SWfMSs) such as Galaxy have become essential infrastructure in bioinformatics, supporting the design, execution, and sharing of complex mult…
How Do Community Smells Influence Self-Admitted Technical Debt in Machine Learning Projects?
Shamse Tasnim Cynthia, Nuri Almarimi, Banani Roy
Community smells reflect poor organizational practices that often lead to socio-technical issues and the accumulation of Self-Admitted Technical Debt (SATD). While prior studies ha…
An Empirical Study on the Impact of Gender Diversity on Code Quality in AI Systems
Shamse Tasnim Cynthia, Banani Roy
The rapid advancement of AI systems necessitates high-quality, sustainable code to ensure reliability and mitigate risks such as bias and technical debt. However, the underrepresen…
Gender Disparities in Contributions, Leadership, and Collaboration: An Exploratory Study on Software Systems Research
Shamse Tasnim Cynthia, Saikat Mondal, Joy Krishan Das +1
Gender diversity enhances research by bringing diverse perspectives and innovative approaches. It ensures equitable solutions that address the needs of diverse populations. However…