Refinements to error-free transformations plus residue override reduce false reports in floating-point residue computation on most tested benchmarks.
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MNAL reduces human effort in bug report labeling by up to 95.8% for readability and 196% for identifiability while improving identification performance and working with various neural models.
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Accurate Residues for Floating-Point Debugging
Refinements to error-free transformations plus residue override reduce false reports in floating-point residue computation on most tested benchmarks.
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Human-Machine Co-Boosted Bug Report Identification with Mutualistic Neural Active Learning
MNAL reduces human effort in bug report labeling by up to 95.8% for readability and 196% for identifiability while improving identification performance and working with various neural models.