Publications | Daniel Ogenrwot

2025

JHU

Case Study of Participatory Data-Driven Approaches to Improve Urban Air Quality in Kampala, Uganda

Deo Okure, Engineer Bainomugisha, Daniel Ogenrwot, and 3 more authors

Urban Health in Africa, 2025

Bib

@article{okure2025case,
  title = {Case Study of Participatory Data-Driven Approaches to Improve Urban Air Quality in Kampala, Uganda},
  author = {Okure, Deo and Bainomugisha, Engineer and Ogenrwot, Daniel and Sserunjogi, Richard and Adrine, Priscah and Okello, Gabriel},
  journal = {Urban Health in Africa},
  pages = {255},
  year = {2025},
  publisher = {JHU Press},
}

arXiv

Refactoring-Aware Patch Integration Across Structurally Divergent Java Forks

Daniel Ogenrwot, and John Businge

2025

Bib PDF

@misc{ogenrwot2025refactoringawarepatchintegrationstructurally,
  title = {Refactoring-Aware Patch Integration Across Structurally Divergent Java Forks},
  author = {Ogenrwot, Daniel and Businge, John},
  year = {2025},
  eprint = {2508.06718},
  archiveprefix = {arXiv},
  primaryclass = {cs.SE},
  award = {The 25th IEEE International Conference on Source Code Analysis and Manipulation (SCAM 2025), to be held in Auckland, New Zealand! },
  award_name = {PREPRINT}
}

arXiv

Structural and Connectivity Patterns in the Maven Central Software Dependency Network

Daniel Ogenrwot, John Businge, and Shaikh Arifuzzaman

2025

Bib

@misc{ogenrwot2025structuralconnectivitypatternsmaven,
  title = {Structural and Connectivity Patterns in the Maven Central Software Dependency Network},
  author = {Ogenrwot, Daniel and Businge, John and Arifuzzaman, Shaikh},
  year = {2025},
  eprint = {2508.13819},
  archiveprefix = {arXiv},
  primaryclass = {cs.SE},
  award = {The 34th International Conference on Software and Data Engineering (SEDE 2025), to be held in New Orleans, Louisiana! },
  award_name = {PREPRINT}
}

arXiv

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

Richard Sserujongi, Daniel Ogenrwot, Nicholas Niwamanya, and 7 more authors

2025

Bib

@misc{sserujongi2025designevaluationscalabledata,
  title = {Design and Evaluation of a Scalable Data Pipeline for AI-Driven Air Quality Monitoring in Low-Resource Settings},
  author = {Sserujongi, Richard and Ogenrwot, Daniel and Niwamanya, Nicholas and Nsimbe, Noah and Bbaale, Martin and Ssempala, Benjamin and Mutabazi, Noble and Wabinyai, Raja Fidel and Okure, Deo and Bainomugisha, Engineer},
  year = {2025},
  eprint = {2508.14451},
  archiveprefix = {arXiv},
  primaryclass = {cs.SE},
  award = {The 34th International Conference on Software and Data Engineering (SEDE 2025), to be held in New Orleans, Louisiana! },
  award_name = {PREPRINT}
}

arXiv

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

Daniel Ogenrwot, and John Businge

2025

Bib

@misc{ogenrwot2025patchtrackcomprehensiveanalysischatgpts,
  title = {PatchTrack: A Comprehensive Analysis of ChatGPT's Influence on Pull Request Outcomes},
  author = {Ogenrwot, Daniel and Businge, John},
  year = {2025},
  eprint = {2505.07700},
  archiveprefix = {arXiv},
  primaryclass = {cs.SE},
}

2024

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

Daniel Ogenrwot, and John Businge

In Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering, 2024

Abs Bib

In recent years, the integration of AI tools such as ChatGPT into software development has grown significantly, reflecting broader trends in AI-assisted workflows [8]. These tools have great potential to improve decision making related to software patches in pull requests (PR), which are vital components of collaborative software development. Specifically, developers are using features such as link sharing in ChatGPT to enhance collaborative practices, streamline code reviews, and make more informed patch integration decisions.
@inproceedings{ogenrwot2024patchtrackASE, author = {Ogenrwot, Daniel and Businge, John}, title = {PatchTrack: Analyzing ChatGPT's Impact on Software Patch Decision-Making in Pull Requests}, year = {2024}, isbn = {9798400712487}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3691620.3695338}, doi = {10.1145/3691620.3695338}, booktitle = {Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering}, pages = {2480–2481}, numpages = {2}, location = {Sacramento, CA, USA}, series = {ASE '24}, }

arXiv

Empirical Investigation of the Relationship Between Design Smells and Role Stereotypes

Daniel Ogenrwot, Joyce Nakatumba-Nabende, John Businge, and 1 more author

2024

Bib

@misc{ogenrwot2024empiricalinvestigationrelationshipdesign,
  title = {Empirical Investigation of the Relationship Between Design Smells and Role Stereotypes},
  author = {Ogenrwot, Daniel and Nakatumba-Nabende, Joyce and Businge, John and Chaudron, Michel R. V.},
  year = {2024},
  eprint = {2406.19254},
  archiveprefix = {arXiv},
  primaryclass = {cs.SE},
}

2023

EGU

Data management in resource-limited settings: Unpacking the role of robust digital solutions for air quality data management in African cities.

Deo Okure, Daniel Ogenrwot, Noah Nsimbe, and 5 more authors

2023

Bib

@techreport{okure2023data,
  title = {Data management in resource-limited settings: Unpacking the role of robust digital solutions for air quality data management in African cities.},
  author = {Okure, Deo and Ogenrwot, Daniel and Nsimbe, Noah and Muyama, Lillian and Adong, Priscilla and Sserunjogi, Richard and Bbaale, Martin and Bainomugisha, Engineer},
  year = {2023},
  institution = {Copernicus Meetings},
  publisher = {EGU23},
  type = {EGU General Assembly 2023, Vienna, Austria, 24-28 April 2023},
  url = {https://doi.org/10.5194/egusphere-egu23-18648},
}

2022

DIB
Seeing the air in detail: Hyperlocal air quality dataset collected from spatially distributed AirQo network

Richard Sserunjogi, Joel Ssematimba, Deo Okure, and 6 more authors

Data in Brief, 2022

Abs Bib

Air pollution is a major global challenge associated with an increasing number of morbidity and mortality from lung cancer, cardiovascular and respiratory diseases, among others. However, there is scarcity of ground monitoring air quality data from Sub-Saharan Africa that can be used to quantify the level of pollution. This has resulted in limited targeted air pollution research and interventions e.g. health impacts, key drivers and sources, economic impacts, among others; ultimately hindering the establishment of effective management strategies. This paper presents a dataset of air quality observations collected from 68 spatially distributed monitoring stations across Uganda. The dataset includes hourly PM2.5 and PM10 data collected from low-cost air quality monitoring devices and one reference grade monitoring device over a period ranging from 2019 to 2020. This dataset contributes towards filling some of the data gaps witnessed over the years in ground level monitored ambient air quality in Sub-Saharan Africa and it can be useful to various policy makers and researchers.
@article{Sserunjogi2022datainbrief, title = {Seeing the air in detail: Hyperlocal air quality dataset collected from spatially distributed AirQo network}, journal = {Data in Brief}, volume = {44}, pages = {108512}, year = {2022}, issn = {2352-3409}, doi = {https://doi.org/10.1016/j.dib.2022.108512}, url = {https://www.sciencedirect.com/science/article/pii/S2352340922007065}, author = {Sserunjogi, Richard and Ssematimba, Joel and Okure, Deo and Ogenrwot, Daniel and Adong, Priscilla and Muyama, Lillian and Nsimbe, Noah and Bbaale, Martin and Bainomugisha, Engineer}, keywords = {Air quality dataset, Sub-Saharan Africa, Air pollution, PM, PM, Particulate matter}, }
FAMECSE
From Undergraduate (Software) Capstone Projects to Start-ups: Challenges and Opportunities in Higher Institutions of Learning

Daniel Ogenrwot, Geoffrey Olok Tabo, Kevin Aber, and 1 more author

In Proceedings of the Federated Africa and Middle East Conference on Software Engineering, 2022

Abs Bib

The capstone project is a fundamental part of almost all science and engineering degrees. It is not only a requirement for the partial fulfillment of an accredited university programme but also a method of assessing the students’ general mastery of concepts, critical thinking, problem-solving, and transferable skills. Annually, final-year undergraduate students offering computing programmes in Uganda build innovative software solutions to real-world problems within and outside their community. Anecdotal evidence indicates that most of those innovations have the potential for commercialization and transformation into technology-based businesses. However, limited progress has been made to commercialize students’ projects, and promising solutions are “buried” within academic reports. To this end, our research aims to explain the challenges and opportunities in the commercialization of students’ capstone projects across two (2) undergraduate computing programmes (Bachelor of Science in Computer Science and Bachelor of Information Technology) offered at Gulu University in Uganda. Using exploratory research design, we reviewed eighty-six (86) capstone projects, curricula, and a facilitated students & stakeholders’ workshop report. This paper articulates factors hindering the commercialization of undergraduate software capstone projects and recommends mitigating measures. It also proposes a framework for extending capstone course design from a traditional curriculum structure to an inclusive industry and community-oriented approach capable of turning ideas into business start-ups. The findings from this research are expected to inform higher institutions of learning in Africa in developing novel pedagogical approaches for orchestrating (software) capstone project courses that are inclusive and profitable beyond the academic setting.
@inproceedings{ogenrwot2022capstone, author = {Ogenrwot, Daniel and Tabo, Geoffrey Olok and Aber, Kevin and Nakatumba-Nabende, Joyce}, title = {From Undergraduate (Software) Capstone Projects to Start-ups: Challenges and Opportunities in Higher Institutions of Learning}, year = {2022}, isbn = {9781450396639}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3531056.3542775}, doi = {10.1145/3531056.3542775}, booktitle = {Proceedings of the Federated Africa and Middle East Conference on Software Engineering}, pages = {73–82}, numpages = {10}, keywords = {Capstone Projects, Commercialization, Software Engineering, Start-ups}, location = {Cairo-Kampala, Egypt}, series = {FAMECSE '22}, }

2021

DIB
Integration of design smells and role-stereotypes classification dataset

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

Data in Brief, 2021

Abs Bib

Design smells are recurring patterns of poorly designed (fragments of) software systems that may hinder maintainability. Role-stereotypes indicate generic responsibilities that classes play in system design. Although the concepts of role-stereotypes and design smells are widely divergent, both are significant contributors to the design and maintenance of software systems. To improve software design and maintainability, there is a need to understand the relationship between design smells and role stereotypes. This paper presents a fine-grained dataset of systematically integrated design smells detection and role-stereotypes classification data. The dataset was created from a collection of twelve (12) real-life open-source Java projects mined from GitHub. The dataset consists of 18 design smells columns and 2,513 Java classes (rows) classified into six (6) role-stereotypes taxonomy. We also clustered the dataset into ten (10) different clusters using an unsupervised learning algorithm. Those clusters are useful for understanding the groups of design smells that often co-occur in a particular role-stereotype category. The dataset is significant for understanding the non-innate relationship between design smells and role-stereotypes.
@article{ogenrwotdatainbrief2021, title = {Integration of design smells and role-stereotypes classification dataset}, journal = {Data in Brief}, volume = {36}, pages = {107125}, year = {2021}, issn = {2352-3409}, doi = {https://doi.org/10.1016/j.dib.2021.107125}, url = {https://www.sciencedirect.com/science/article/pii/S2352340921004091}, author = {Ogenrwot, Daniel and Nakatumba-Nabende, Joyce and Chaudron, Michel R.V.}, keywords = {Software design, Role-stereotype, Design smells, Software quality}, }

2020

ACSE
Comparison of Occurrence of Design Smells in Desktop and Mobile Applications

Daniel Ogenrwot, Joyce Nakatumba-Nabende, and Michel RV Chaudron

Proceedings of the 2020 African Conference on Software Engineering (ACSE), 2020

Abs Bib

Design smells are symptoms of poor solutions to recurring design problems in a software system. Those symptoms have a direct negative impact on software quality by making it difficult to comprehend and maintain. In this paper we compare the occurrence of design smells between different technological ecosystems: windows/desktop and android/mobile. This knowledge is significant for various software maintenance activities such as program quality assurance and refactoring. To supplement previous findings, our study aimed at (a) under- standing if and how the relationship among design smells differs across windows and mobile applications and (b) determining the groups of design smells that tend to occur frequently together and the magnitude of their occurrence in windows and mobile applications. In this study, we explored the use of statistics and unsupervised learning on a dataset consisting of twelve (12) Java- based open-source projects mined from GitHub. We identified fifteen (15) most frequent design smells across desktop and mobile applications. Additionally, a clustering technique revealed which groups of design smells that often co-occur. Specifically, SpeculativeGenerality, SwissArmyKnife and LongParameterList, ClassDataShouldBePrivate are observed to occur frequently together in desktop and mobile applications.
@article{ogenrwot2020comparison, title = {Comparison of Occurrence of Design Smells in Desktop and Mobile Applications}, author = {Ogenrwot, Daniel and Nakatumba-Nabende, Joyce and Chaudron, Michel RV}, year = {2020}, publisher = {Ceur Workshop Proceedings}, volume = {2689}, journal = {Proceedings of the 2020 African Conference on Software Engineering (ACSE)}, }