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: International Journal on Smart Sensing and Intelligent Systems
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
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© 2025 Pooja Bagane, Chahak Sengar, Sumedh Dongre, Siddharth Prabhakar, Obsa Amenu Jebessa, published by International Journal on Smart Sensing and Intelligent Systems
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.