A code change‐oriented approach to just‐in‐time defect prediction with multiple input semantic fusion

Recent research found that fine‐tuning pre‐trained models is superior to training models from scratch in just‐in‐time (JIT) defect prediction. However, existing approaches using pre‐trained models have their limitations. First, the input length is constrained by the pre‐trained models.Secondly, the...

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Veröffentlicht in:	Expert systems 2024-12, Vol.41 (12), p.n/a
Hauptverfasser:	Huang, Teng, Yu, Hui‐Qun, Fan, Gui‐Sheng, Huang, Zi‐Jie, Wu, Chen‐Yu
Format:	Artikel
Sprache:	eng
Schlagworte:	deep learning defect prediction Defects just‐in‐time Performance measurement Semantics software defect
Online-Zugang:	Volltext
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