arXiv (All)
open access
Self-Evolving Static Analysis via LLM Pseudo-Labeling
Security bugs often slip past static analysis not because they are impossible to detect, but because detection rules have not yet been written for the code in front of us. New frameworks, APIs, and coding idioms continually create such gaps, leaving developers to discover failures and manually encod
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Towards Counterfactual Explanation and Assertion Inference for CPS Debugging#2684
- Using LLMs to Adjudicate Static-Analysis Alerts with Error Reduction Techniques#363350
- AIRA: AI-Induced Risk Audit: A Structured Inspection Framework for AI-Generated Code#120593
- Memoir: Learning, Verifying, and Evolving False-Positive Memories for Static Application Security Testing Tools#441692
- PITMuS: A Tool for Automated Bug Dataset Generation via Source-Level Mutant Reconstruction#216893
Record · ID 1422976
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive