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

Artikel-Kategorie: Research Article

Online veröffentlicht: 25. März 2025

Eingereicht: 10. Jan. 2025

DOI: https://doi.org/10.2478/ijssis-2025-0012

Schlüsselwörter

technical debt, self-admitted technical debt, machine learning, random forest, gradient boosting, long short-term memory, gated recurrent unit, Java codebases, software engineering, automated detection

© 2025 Dr. Pooja Bagane et al., published by Sciendo

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