Training parameters setting for pre-trained Baseline, Deep Learning, and transformer Models on Bug Dataset.

Training parameters setting for pre-trained Baseline, Deep Learning, and transformer Models on Bug Dataset.

<p>Training parameters setting for pre-trained Baseline, Deep Learning, and transformer Models on Bug Dataset.</p>

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Sajid Ullah (8299908) (author)
مؤلفون آخرون: M. Irfan Uddin (8909933) (author), Muhammad Adnan (678952) (author), Ala Abdulsalam Alarood (21526803) (author), Abdulkream Alsulami (21526806) (author), Safa Habibullah (21526809) (author)
منشور في: 2025
الموضوعات:
Genetics
Mental Health
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
transfer learning approach
proposed approach detects
naive bayes ).
methodology involves developing
machine learning methods
deep learning models
admitted technical debt
software comments associated
create software systems
research &# 8217
previous research focuses
detecting bugs alone
categorising bugs based
software quality assessment
performance evaluation criteria
designated satd examples
software engineering
comparative assessment
software defects
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work presents
without identifying
transformer model
suggested method
software maintenance
slightly lower
significant implications
resource allocation
mozilla firefox
including apache
direct impact
depth exploration
current methodologies
concurrent identification
comprehensive method
business procedures
bug instances
baseline model
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