Automatic detection of technical debt in large-scale java codebases: a multi-model deep learning methodology for enhanced software quality
Authors
Pooja Bagane
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
DOI: https://doi.org/10.2478/ijssis-2025-0012 | Journal eISSN: 1178-5608
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
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© 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.