DebugRepair improves LLM-based automated program repair by adding test semantic purification, simulated instrumentation, and debugging-driven conversational repair, fixing 224 Defects4J bugs with GPT-3.5 (26.2% above prior SOTA) and 295 with DeepSeek-V3.
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DynaFix iteratively feeds execution-level dynamic information such as variable states and control flows into LLM prompts to repair 186 bugs on Defects4J, a 10% gain over baselines including 38 previously unrepaired cases.
V2E automates PoC generation, triggerability and profitability validation, and iterative refinement using LLMs to confirm exploitable smart contract vulnerabilities, outperforming baselines on 264 labeled contracts.
citing papers explorer
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DebugRepair: Enhancing LLM-Based Automated Program Repair via Self-Directed Debugging
DebugRepair improves LLM-based automated program repair by adding test semantic purification, simulated instrumentation, and debugging-driven conversational repair, fixing 224 Defects4J bugs with GPT-3.5 (26.2% above prior SOTA) and 295 with DeepSeek-V3.
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DynaFix: Iterative Automated Program Repair Driven by Execution-Level Dynamic Information
DynaFix iteratively feeds execution-level dynamic information such as variable states and control flows into LLM prompts to repair 186 bugs on Defects4J, a 10% gain over baselines including 38 previously unrepaired cases.
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V2E: Validating Smart Contract Vulnerabilities through Profit-driven Exploit Generation and Execution
V2E automates PoC generation, triggerability and profitability validation, and iterative refinement using LLMs to confirm exploitable smart contract vulnerabilities, outperforming baselines on 264 labeled contracts.