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Automatic detection of technical debt in large-scale java codebases: a multi-model deep learning methodology for enhanced software quality Cover

Automatic detection of technical debt in large-scale java codebases: a multi-model deep learning methodology for enhanced software quality

Open Access
|Mar 2025

Authors

Pooja Bagane

pooja.bagane@gmail.com

Department of Computer Science and Engineering, Symbiosis Institute of Technology-Pune Campus, Symbiosis International (Deemed University), Pune, India

Chahak Sengar

Department of Computer Science and Engineering, Symbiosis Institute of Technology-Pune Campus, Symbiosis International (Deemed University), Pune, India

Sumedh Dongre

Department of Computer Science and Engineering, Symbiosis Institute of Technology-Pune Campus, Symbiosis International (Deemed University), Pune, India

Siddharth Prabhakar

Department of Computer Science and Engineering, Symbiosis Institute of Technology-Pune Campus, Symbiosis International (Deemed University), Pune, India

Obsa Amenu Jebessa

Department of Information Technology, Jimma Institute of Technology, Jimma, Ethiopia
Language: English
Submitted on: Jan 10, 2025
Published on: Mar 25, 2025
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 times per year

© 2025 Pooja Bagane, Chahak Sengar, Sumedh Dongre, Siddharth Prabhakar, Obsa Amenu Jebessa, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.