10 publications from 2022 onwards — For the latest publication list, please refer to Googe Scholar

2026

Patchtrack: a comprehensive analysis of chatgpt’s influence on pull request outcomes

Daniel Ogenrwot, John Businge

AIware 2026 — Benchmark & Dataset Track (co-located with FSE 2026) 2026

The rapid adoption of large language models (LLMs) like ChatGPT has introduced new dynamics in software development, particularly within pull request workflows. We analyze 338 pull requests from 255 GitHub repositories containing self-admitted ChatGPT usage, comprising 645 AI-generated snippets and 3,486 developer-authored patches.

[Paper] [Dataset & Code]

Patchtrack: a comprehensive analysis of chatgpt’s influence on pull request outcomes

Daniel Ogenrwot, John Businge

AIware 2026 — Benchmark & Dataset Track (co-located with FSE 2026) 2026

The rapid adoption of large language models (LLMs) like ChatGPT has introduced new dynamics in software development, particularly within pull request workflows. We analyze 338 pull requests from 255 GitHub repositories containing self-admitted ChatGPT usage, comprising 645 AI-generated snippets and 3,486 developer-authored patches.

[Paper] [Dataset & Code]

AgenticFlict: A Large-Scale Dataset of Merge Conflicts in AI Coding Agent Pull Requests on GitHub

Daniel Ogenrwot, John Businge

AIware 2026 — Benchmark & Dataset Track (co-located with FSE 2026) 2026

Large-scale dataset of 142K+ agentic pull requests from 59K+ repositories, identifying 29K PRs with merge conflicts and extracting 336K+ fine-grained conflict regions across AI coding agents (Copilot, Devin, Cursor, and others).

[Preprint] [Dataset & Code]

AgenticFlict: A Large-Scale Dataset of Merge Conflicts in AI Coding Agent Pull Requests on GitHub

Daniel Ogenrwot, John Businge

AIware 2026 — Benchmark & Dataset Track (co-located with FSE 2026) 2026

Large-scale dataset of 142K+ agentic pull requests from 59K+ repositories, identifying 29K PRs with merge conflicts and extracting 336K+ fine-grained conflict regions across AI coding agents (Copilot, Devin, Cursor, and others).

[Preprint] [Dataset & Code]

How AI Coding Agents Modify Code: A Large-Scale Study of GitHub Pull Requests

Daniel Ogenrwot, John Businge

MSR 2026 — Mining Challenge Track 2026

Large-scale empirical comparison of ~24,000 merged agentic pull requests against 5,000 human-authored PRs using the AIDev dataset, examining additions, deletions, commits, and files modified. Finds that AI-generated PRs show substantially higher commit counts and slightly superior description-to-code alignment across multiple similarity measures.

[Paper]

How AI Coding Agents Modify Code: A Large-Scale Study of GitHub Pull Requests

Daniel Ogenrwot, John Businge

MSR 2026 — Mining Challenge Track 2026

Large-scale empirical comparison of ~24,000 merged agentic pull requests against 5,000 human-authored PRs using the AIDev dataset, examining additions, deletions, commits, and files modified. Finds that AI-generated PRs show substantially higher commit counts and slightly superior description-to-code alignment across multiple similarity measures.

[Paper]

Design and Evaluation of a Scalable Data Pipeline for AI-Driven Air Quality Monitoring in Low-Resource Settings

Richard Sserunjogi, Daniel Ogenrwot, Nicholas Niwamanya, Noah Nsimbe, Martin Bbaale, Benjamin Ssempala, Noble Mutabazi, Raja Fidel Wabinyai, Deo Okure, Engineer Bainomugisha

Software and Data Engineering (SEDE) 2026

Cloud-native ETL system leveraging Apache Airflow, Kafka, and BigQuery for processing air quality data across African urban deployments.

[Paper]

Design and Evaluation of a Scalable Data Pipeline for AI-Driven Air Quality Monitoring in Low-Resource Settings

Richard Sserunjogi, Daniel Ogenrwot, Nicholas Niwamanya, Noah Nsimbe, Martin Bbaale, Benjamin Ssempala, Noble Mutabazi, Raja Fidel Wabinyai, Deo Okure, Engineer Bainomugisha

Software and Data Engineering (SEDE) 2026

Cloud-native ETL system leveraging Apache Airflow, Kafka, and BigQuery for processing air quality data across African urban deployments.

[Paper]

Structural and Connectivity Patterns in the Maven Central Software Dependency Network

Daniel Ogenrwot, John Businge, Shaikh Arifuzzaman

Software and Data Engineering (SEDE) 2026

Study of the Maven Central ecosystem using network science, analyzing 1.3M nodes and 20.9M edges to reveal scale-free topology and systemic risks from critical infrastructure hubs.

[Paper]

Structural and Connectivity Patterns in the Maven Central Software Dependency Network

Daniel Ogenrwot, John Businge, Shaikh Arifuzzaman

Software and Data Engineering (SEDE) 2026

Study of the Maven Central ecosystem using network science, analyzing 1.3M nodes and 20.9M edges to reveal scale-free topology and systemic risks from critical infrastructure hubs.

[Paper]

2025

Refactoring-Aware Patch Integration Across Structurally Divergent Java Forks

Daniel Ogenrwot, John Businge

2025 IEEE International Conference on Source Code Analysis & Manipulation (SCAM) 2025 Distinguished Artifact Award

RePatch addresses structural drift in divergent software variants through refactoring-aware patch integration, achieving 52.8% success on previously failing patches.

[Paper] [Code]

Refactoring-Aware Patch Integration Across Structurally Divergent Java Forks

Daniel Ogenrwot, John Businge

2025 IEEE International Conference on Source Code Analysis & Manipulation (SCAM) 2025 Distinguished Artifact Award

RePatch addresses structural drift in divergent software variants through refactoring-aware patch integration, achieving 52.8% success on previously failing patches.

[Paper] [Code]

PatchTrack: A Comprehensive Analysis of ChatGPT's Influence on Pull Request Outcomes

Daniel Ogenrwot, John Businge

Empirical Software Engineering (EMSE) 2025

Analysis of 338 pull requests examining AI-generated code integration, revealing a median adoption rate of 25% and iterative refinement patterns in software development workflows.

[Paper] [Preprint]

PatchTrack: A Comprehensive Analysis of ChatGPT's Influence on Pull Request Outcomes

Daniel Ogenrwot, John Businge

Empirical Software Engineering (EMSE) 2025

Analysis of 338 pull requests examining AI-generated code integration, revealing a median adoption rate of 25% and iterative refinement patterns in software development workflows.

[Paper] [Preprint]

2024

PatchTrack: Analyzing ChatGPT's Impact on Software Patch Decision-Making in Pull Requests

Daniel Ogenrwot, John Businge

39th IEEE/ACM International Conference on Automated Software Engineering (ASE) 2024

Empirical study investigating how ChatGPT-generated patches influence pull request acceptance decisions, examining 338 pull requests across open-source projects.

[Paper]

PatchTrack: Analyzing ChatGPT's Impact on Software Patch Decision-Making in Pull Requests

Daniel Ogenrwot, John Businge

39th IEEE/ACM International Conference on Automated Software Engineering (ASE) 2024

Empirical study investigating how ChatGPT-generated patches influence pull request acceptance decisions, examining 338 pull requests across open-source projects.

[Paper]

Empirical Investigation of the Relationship Between Design Smells and Role Stereotypes

Daniel Ogenrwot, Joyce Nakatumba-Nabende, John Businge, Michel R.V. Chaudron

arXiv 2024

Analysis of 11,350 classes from 30 repositories revealing that design smell prevalence varies across role-stereotypes and application ecosystems.

[Paper]

Empirical Investigation of the Relationship Between Design Smells and Role Stereotypes

Daniel Ogenrwot, Joyce Nakatumba-Nabende, John Businge, Michel R.V. Chaudron

arXiv 2024

Analysis of 11,350 classes from 30 repositories revealing that design smell prevalence varies across role-stereotypes and application ecosystems.

[Paper]

2022

From Undergraduate (Software) Capstone Projects to Start-ups: Challenges and Opportunities in Higher Institutions of Learning

Daniel Ogenrwot, Geoffrey Olok Tabo, Kevin Aber, Joyce Nakatumba-Nabende

Federated Africa and Middle East Conference on Software Engineering (FAMECSE) 2022

[Paper]

From Undergraduate (Software) Capstone Projects to Start-ups: Challenges and Opportunities in Higher Institutions of Learning

Daniel Ogenrwot, Geoffrey Olok Tabo, Kevin Aber, Joyce Nakatumba-Nabende

Federated Africa and Middle East Conference on Software Engineering (FAMECSE) 2022

[Paper]