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Real Faults in Deep Learning Fault Benchmarks: How Real Are They?

Jahangirova, Gunel et al.
arXiv (All) · Papers
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artificial-intelligencemachine-learningsoftware-engineering
As the adoption of Deep Learning (DL) systems continues to rise, an increasing number of approaches are being proposed to test these systems, localise faults within them, and repair those faults. The best attestation of effectiveness for such techniques is an evaluation that showcases their capabili
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