Awesome Bug Detection

Key papers

• How Can ChatGPT Support Human Security Testers to Help Mitigate Supply Chain Attacks? (2023)
  Ying Zhang et al.
  8.58
• LLMs in Software Security: A Survey of Vulnerability Detection Techniques and Insights (2025)
  Ze Sheng et al.
  7.50
• To Err is Machine: Vulnerability Detection Challenges LLM Reasoning (2024)
  Benjamin Steenhoek et al.
  7.16
• IRIS: LLM-Assisted Static Analysis for Detecting Security Vulnerabilities (2024)
  Ziyang Li et al.
  7.00
• PlotGen: Multi-Agent LLM-based Scientific Data Visualization via Multimodal Feedback (2025)
  Kanika Goswami et al.
  6.64
• Agora: Toward Autonomous Bug Detection in Production-Level Consensus Protocols with LLM Agents (2026)
  Xiang Liu et al.
  6.46
• Security Weaknesses of Copilot-Generated Code in GitHub Projects: An Empirical Study (2023)
  Yujia Fu et al.
  6.13
• Fuzzing BusyBox: Leveraging LLM and Crash Reuse for Embedded Bug Unearthing (2024)
  Asmita et al.
  6.02
• PythonPal: Enhancing Online Programming Education through Chatbot-Driven Personalized Feedback (2025)
  Sirinda Palahan
  5.96
• Benchmarking Prompt Engineering Techniques for Secure Code Generation with GPT Models (2025)
  Marc Bruni et al.
  5.90
• SVA-ICL: Improving LLM-based Software Vulnerability Assessment via In-Context Learning and Information Fusion (2025)
  Chaoyang Gao et al.
  5.76
• Fully Autonomous Programming using Iterative Multi-Agent Debugging with Large Language Models (2025)
  Anastasiia Grishina and Vadim Liventsev and Aki H\"arm\"a and Leon Moonen
  5.65
• SecureFalcon: Are We There Yet in Automated Software Vulnerability Detection with LLMs? (2023)
  Mohamed Amine Ferrag et al.
  5.58
• From Vulnerabilities to Remediation: A Systematic Literature Review of LLMs in Code Security (2024)
  Enna Basic et al.
  5.52
• CODESIM: Multi-Agent Code Generation and Problem Solving through Simulation-Driven Planning and Debugging (2025)
  Md. Ashraful Islam et al.
  5.46
• TOGLL: Correct and Strong Test Oracle Generation with LLMs (2024)
  Soneya Binta Hossain and Matthew Dwyer
  5.40
• Quality In, Quality Out: Investigating Training Data's Role in AI Code Generation (2025)
  Cristina Improta et al.
  5.29
• What's Wrong with Your Code Generated by Large Language Models? An Extensive Study (2024)
  Shihan Dou et al.
  5.20
• KernelGPT: Enhanced Kernel Fuzzing via Large Language Models (2024)
  Chenyuan Yang et al.
  5.18
• BitsAI-CR: Automated Code Review via LLM in Practice (2025)
  Tao Sun et al.
  5.18
• Alibaba LingmaAgent: Improving Automated Issue Resolution via Comprehensive Repository Exploration (2024)
  Yingwei Ma and Qingping Yang and Rongyu Cao and Binhua Li and Fei Huang and Yongbin Li
  5.15
• Towards Translating Real-World Code with LLMs: A Study of Translating to Rust (2024)
  Hasan Ferit Eniser et al.
  5.09
• AI-powered Code Review with LLMs: Early Results (2024)
  Zeeshan Rasheed et al.
  5.04
• Willing but Unable: Separating Refusal from Capability in Code LLMs via Abliteration (2026)
  Cristina Carleo et al.
  5.01
• Securing Code Understanding: Detecting Natural Backdoor Vulnerability in Code Language Models (2026)
  Yuchen Chen et al.
  5.01
• Context-Based Adversarial Attacks on AI Code Generators: Vulnerability Analysis and Implications (2026)
  Walther A. Del Orbe et al.
  5.01
• Minimal Prompt Perturbations Lead to Code Vulnerabilities: Prompt Fragility and Hidden-State Signals in Coding LLMs (2026)
  Alexander Sternfeld et al.
  4.95
• On Benchmarking Code LLMs for Android Malware Analysis (2025)
  Yiling He et al.
  4.93
• Validating Network Protocol Parsers with Traceable RFC Document Interpretation (2025)
  Mingwei Zheng et al.
  4.93
• Enhancing Software Vulnerability Detection Using Code Property Graphs and Convolutional Neural Networks (2025)
  Amanpreet Singh Saimbhi
  4.87
• Combining Language and App UI Analysis for the Automated Assessment of Bug Reproduction Steps (2025)
  Junayed Mahmud et al.
  4.82
• LLM4CVE: Enabling Iterative Automated Vulnerability Repair with Large Language Models (2025)
  Mohamad Fakih et al.
  4.76
• Test Wars: A Comparative Study of SBST, Symbolic Execution, and LLM-Based Approaches to Unit Test Generation (2025)
  Azat Abdullin et al.
  4.76
• Code Change Intention, Development Artifact and History Vulnerability: Putting Them Together for Vulnerability Fix Detection by LLM (2025)
  Xu Yang et al.
  4.76
• Are Large Language Models Memorizing Bug Benchmarks? (2024)
  Daniel Ramos et al.
  4.65
• ACFIX: Guiding LLMs with Mined Common RBAC Practices for Context-Aware Repair of Access Control Vulnerabilities in Smart Contracts (2024)
  Lyuye Zhang and Kaixuan Li and Kairan Sun and Daoyuan Wu and Ye Liu and Haoye Tian and Yang Liu
  4.63
• Learning Software Bug Reports: A Systematic Literature Review (2025)
  Guoming Long et al.
  4.58
• On the Challenges of Fuzzing Techniques via Large Language Models (2024)
  Linghan Huang et al.
  4.57
• A Preliminary Study of Large Language Models for Multilingual Vulnerability Detection (2025)
  Junji Yu et al.
  4.47
• LLM4SZZ: Enhancing SZZ Algorithm with Context-Enhanced Assessment on Large Language Models (2025)
  Lingxiao Tang et al.
  4.42
• Benchmarking LLM for Code Smells Detection: OpenAI GPT-4.0 vs DeepSeek-V3 (2025)
  Ahmed R. Sadik et al.
  4.42
• VeriDebug: A Unified LLM for Verilog Debugging via Contrastive Embedding and Guided Correction (2025)
  Ning Wang et al.
  4.42
• SPOQ: Specialist Orchestrated Queuing for Multi-Agent Software Engineering (2026)
  Royce Carbowitz et al.
  4.39
• Decoupled Smart Contract Audits: Lightweight LLM Framework via Distillation and Aggregation (2026)
  Bagus Rakadyanto Oktavianto Putra et al.
  4.39
• Learn from Your Mistakes: Tree-like Self-Play for Secure Code LLMs (2026)
  Wenqi Chen et al.
  4.39
• FLARE: Fine-Grained Diagnostic Feedback for LLM Code Refinement (2026)
  Yinsheng Yao et al.
  4.39
• Multi-task LLMs for Bug Classification: Efficient Inference with Auxiliary Decoding Heads (2026)
  Nikolai Rozanov
  4.39
• Data-aware Static Analysis: Improving Detection of Semantic Faults in Machine Learning Code Using Data Characteristics (2026)
  Willem Meijer et al.
  4.39
• SEC-bench Pro: Can Language Models Solve Long-Horizon Software Security Tasks? (2026)
  Hwiwon Lee et al.
  4.33
• ConVer: Using Contracts and Loop Invariant Synthesis for Scalable Formal Software Verification (2026)
  Muhammad A. A. Pirzada et al.
  4.33
• ProDebug: An Automated Debugging System for Prolog (2026)
  Ricardo Brancas et al.
  4.33
• AssertLLM2: A Comprehensive LLM Benchmark for Assertion Generation from Design Specifications (2026)
  Yuchao Wu et al.
  4.33
• Poison with Style: A Practical Poisoning Attack on Code Large Language Models (2026)
  Khang Tran et al.
  4.33
• Multi-Agent LLM-based Metamorphic Testing for REST APIs (2026)
  Shehroz Khan et al.
  4.33
• Learning the Error Patterns of Language Models (2026)
  Jinwoo Kim et al.
  4.33
• Functional Entropy: Predicting Functional Correctness in LLM-Generated Code with Uncertainty Quantification (2026)
  Dylan Bouchard et al.
  4.33
• Towards Demystifying and Repairing LLM-in-the-Loop Vulnerabilities (2026)
  Yujie Ma et al.
  4.33
• Usability Analysis of Configurator User Interfaces with Multimodal Large Language Models (2026)
  Sebastian Lubos et al.
  4.33
• Inferring Code Correctness from Specification (2026)
  Tambon Florian et al.
  4.33
• Projectional Decoding: Towards Semantic-Aware LLM Generation (2026)
  Boqi Chen et al.
  4.33