BIC-Hunter combines confident learning for label denoising and GCNs on homogeneous graphs to identify bug-inducing commits, reporting gains of 6.16-7.13% on Recall@K and 8.43-32.82% on MFR over prior methods.
Detecting the root cause code lines in bug-fixing commits by heterogeneous graph learning
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Confident Learning-based Network for Detecting Bug-Inducing Commits on SZZ with Noisy Labels
BIC-Hunter combines confident learning for label denoising and GCNs on homogeneous graphs to identify bug-inducing commits, reporting gains of 6.16-7.13% on Recall@K and 8.43-32.82% on MFR over prior methods.