8 papers
Prompt Quality and Pull Request Outcomes: A Stage-Based Empirical Study of LLM-Assisted Development
Richard Sserunjogi, Daniel Ogenrwot, John Businge
Large language model (LLM)-powered tools such as ChatGPT are increasingly used in collaborative software engineering workflows, yet little is known about how prompt structure influ…
AgenticFlict: A Large-Scale Dataset of Merge Conflicts in AI Coding Agent Pull Requests on GitHub
Daniel Ogenrwot, John Businge
Software Engineering 3.0 marks a paradigm shift in software development, in which AI coding agents are no longer just assistive tools but active contributors. While prior empirical…
How AI Coding Agents Modify Code: A Large-Scale Study of GitHub Pull Requests
Daniel Ogenrwot, John Businge
AI coding agents are increasingly acting as autonomous contributors by generating and submitting pull requests (PRs). However, we lack empirical evidence on how these agent-generat…
PatchTrack: A Comprehensive Analysis of ChatGPT's Influence on Pull Request Outcomes
Daniel Ogenrwot, John Businge
The rapid adoption of large language models (LLMs) like ChatGPT has introduced new dynamics in software development, particularly within pull request workflows. While prior researc…
MOVis: A Visual Analytics Tool for Surfacing Missed Patches Across Software Variants
Jorge Gonzalo Delgado Cervantes, John Businge, Daniel Ogenrwot
Clone-and-own development produces families of related software variants that evolve independently. As variants diverge, important fixes applied in one repository are often missing…
Design and Evaluation of a Scalable Data Pipeline for AI-Driven Air Quality Monitoring in Low-Resource Settings
Richard Sserujongi, Daniel Ogenrwot, Nicholas Niwamanya +7
The increasing adoption of low-cost environmental sensors and AI-enabled applications has accelerated the demand for scalable and resilient data infrastructures, particularly in da…