The Data Problem in Software Vulnerability Analysis: Artifacts, Quality, and Consumption
This work investigates the data behind vulnerability analysis through a dataset-centric taxonomy that separates what an artifact is (code, metadata, patches, tests/PoCs, reasoning, traces), how good it is (realism, label evidence, scale, diversity, leakage, availability), and what it is used for.
Yu Nong, Yao Du, Tian-Xiang Xu et al.
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