Better Understanding, Better Fixes? A Study of Hallucination in LLM-based Automated Program Repair

arXiv:2609.04909 · cs.SE, cs.AI · Submitted 2026-09-04 · Read on arXiv

cs.SE, cs.AI

Submitted: 2026-09-04

Updated: 2026-09-28

Code: https://github.com/Cxm211/LLM_Hallucination

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Hallucination — 233× in this paper · explained in 3 episodes
• F1 Score — 14× in this paper · explained in 3 episodes
• Grounding — 13× in this paper · explained in 3 episodes
• Benchmark — 9× in this paper · explained in 2 episodes
• Trace — 5× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 4× in this paper · explained in 6 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Agentic Task — 1× in this paper · explained in 1 episode
• Agentic Tasks — 1× in this paper · explained in 1 episode
• Annotator Agreement — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Causal Understanding — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Formal Verification — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Hallucination Detection — 1× in this paper · explained in 2 episodes
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Structural Integrity — 1× in this paper · explained in 3 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity
• Understanding Software Engineering Agents: A Study of Thought-Action-Result Trajectories
• Evaluating Large Language Models Trained on Code
• Agentic Bug Reproduction for Effective Automated Program Repair at Google
• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• When Agents go Astray: Course-Correcting SWE Agents with PRMs
• Red Teaming Program Repair Agents: When Correct Patches can Hide Vulnerabilities
• De-Hallucinator: Mitigating LLM Hallucinations in Code Generation Tasks via Iterative Grounding
• Hallucinations in Large Multilingual Translation Models
• Hallucination by Code Generation LLMs: Taxonomy, Benchmarks, Mitigation, and Challenges
• RepoRepair: Leveraging Code Documentation for Repository-Level Automated Program Repair
• HAFixAgent: History-Aware Program Repair Agent
• When "Correct" Is Not Safe: Can We Trust Functionally Correct Patches Generated by Code Agents?
• From Guessing to Seeing: Enhancing LLM-Based Program Repair via Trace-Guided Multi-strategy Debate

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• PackMonitor: Enabling Zero Package Hallucinations Through Decoding-Time Monitoring
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