Method-Based and BERT-Based Bug Prediction in Open Source Software: A Comparative Study

dc.contributor.author	Sivan, Sadman Mehedi
dc.contributor.author	Abir, Mohammad
dc.date.accessioned	2026-06-17T08:35:34Z
dc.date.issued	2025-10-25
dc.description	Supervised by Mr. Nazmul Hossain, Assistant Professor, Department of Computer Science and Engineering (CSE) Islamic University of Technology (IUT) Board Bazar, Gazipur, Bangladesh This thesis is submitted in partial fulfillment of the requirement for the degree of Bachelor of Science in Computer Science and Engineering, 2025
dc.description.abstract	Bug prediction is essential for maintaining software quality, but manual processes are inefficient and error-prone. This study compares traditional method-level bug prediction techniques with modern NLP approaches, focusing on pre-trained lan guage models like BERT. Using a GitHub issues dataset, we analyze the effective ness, challenges, and practical implications of both methodologies. Our findings show that while method-level approaches remain robust when historical data is available, BERT-based models provide competitive performance and unique ad vantages, particularly in scenarios lacking detailed code history
dc.identifier.uri	https://repository.iutoic-dhaka.edu/handle/123456789/2599
dc.language.iso	en
dc.publisher	Department of Computer Science and Engineering(CSE), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh
dc.title	Method-Based and BERT-Based Bug Prediction in Open Source Software: A Comparative Study
dc.type	Thesis

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