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>

Saved in:

Bibliographic Details
Main Author:	Sajid Ullah (8299908) (author)
Other Authors:	M. Irfan Uddin (8909933) (author), Muhammad Adnan (678952) (author), Ala Abdulsalam Alarood (21526803) (author), Abdulkream Alsulami (21526806) (author), Safa Habibullah (21526809) (author)
Published:	2025
Subjects:	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 xlink "> 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
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items