D-2A

The 'D2A' dataset/benchmark is used to evaluate the effectiveness of automated false positive mitigation methods in Static Application Security Testing (SAST) by providing a collection of code snippets and associated warnings.

Papers using D-2A (4)

Utilizing Precise and Complete Code Context to Guide LLM in Automatic False Positive Mitigation2024 · 2 citesSAFE: Advancing Large Language Models in Leveraging Semantic and Syntactic Relationships for Software Vulnerability Detection2024D2A: A Dataset Built for AI-Based Vulnerability Detection Methods Using Differential Analysis2021 · 135 citesVulBERTa: Simplified Source Code Pre-Training for Vulnerability Detection2022 · 135 cites