Software defect prediction at file level: A hybrid deep learning approach combining source code metrics and semantic features

The necessity for trustworthy Software Defect Prediction (SDP) models is highlighted by the increasing complexity of contemporary software systems. These models facilitate the effective use of scarce testing resources by early detection of potentially defective modules. Although deep learning has de...

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Bibliografiska uppgifter

Huvudupphov:	Esrael GEREMEW
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	ICI Publishing House 2026-03-01
Serie:	Revista Română de Informatică și Automatică
Ämnen:	software defect prediction deep learning source code metrics semantic features abstract syntax trees feature representation learning
Länkar:	https://rria.ici.ro/documents/1417/Art_Geremew_Wagaw.pdf
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