Awesome Code Generation

Key papers

• A Survey on Large Language Models for Code Generation (2024)
  Juyong Jiang et al.
  9.98
• How Can ChatGPT Support Human Security Testers to Help Mitigate Supply Chain Attacks? (2023)
  Ying Zhang et al.
  8.58
• REPOT: Recoverable Program-of-Thought via Checkpoint Repair (2026)
  Parsa Mazaheri
  8.51
• CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation (2026)
  Weinan Dai et al.
  8.17
• An Empirical Study of Retrieval-Augmented Code Generation: Challenges and Opportunities (2025)
  Zezhou Yang et al.
  7.29
• PlotGen: Multi-Agent LLM-based Scientific Data Visualization via Multimodal Feedback (2025)
  Kanika Goswami et al.
  7.06
• Spec2RTL-Agent: Automated Hardware Code Generation from Complex Specifications Using LLM Agent Systems (2025)
  Zhongzhi Yu et al.
  7.06
• IRIS: LLM-Assisted Static Analysis for Detecting Security Vulnerabilities (2024)
  Ziyang Li et al.
  7.00
• RTL++: Graph-enhanced LLM for RTL Code Generation (2025)
  Mohammad Akyash et al.
  6.58
• GPIoT: Tailoring Small Language Models for IoT Program Synthesis and Development (2025)
  Leming Shen et al.
  6.47
• A Showdown of ChatGPT vs DeepSeek in Solving Programming Tasks (2025)
  Ronas Shakya et al.
  6.23
• AI-Powered, But Power-Hungry? Energy Efficiency of LLM-Generated Code (2025)
  Lola Solovyeva et al.
  6.17
• Bridging the Editing Gap in LLMs: FineEdit for Precise and Targeted Text Modifications (2025)
  Yiming Zeng and Wanhao Yu and Zexin Li and Tao Ren and Yu Ma and Jinghan Cao and Xiyan Chen and Tingting Yu
  6.17
• Security Weaknesses of Copilot-Generated Code in GitHub Projects: An Empirical Study (2023)
  Yujia Fu et al.
  6.13
• A Survey on Evaluating Large Language Models in Code Generation Tasks (2024)
  Liguo Chen et al.
  6.08
• VRank: Enhancing Verilog Code Generation from Large Language Models via Self-Consistency (2025)
  Zhuorui Zhao et al.
  5.90
• Benchmarking Prompt Engineering Techniques for Secure Code Generation with GPT Models (2025)
  Marc Bruni et al.
  5.90
• Verus-SpecGym: An Agentic Environment for Evaluating Specification Autoformalization (2026)
  Anmol Agarwal et al.
  5.81
• 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
• Translating Regulatory Clauses into Executable Codes for Building Design Checking via Large Language Model Driven Function Matching and Composing (2023)
  Zhe Zheng et al.
  5.63
• The Impact of Large Language Models on Open-source Innovation: Evidence from GitHub Copilot (2024)
  Doron Yeverechyahu et al.
  5.62
• COFFE: A Code Efficiency Benchmark for Code Generation (2025)
  Yun Peng et al.
  5.59
• LLM-Generated Microservice Implementations from RESTful API Definitions (2025)
  Saurabh Chauhan et al.
  5.59
• 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
• Scaling Text-Rich Image Understanding via Code-Guided Synthetic Multimodal Data Generation (2025)
  Yue Yang et al.
  5.46
• TOGLL: Correct and Strong Test Oracle Generation with LLMs (2024)
  Soneya Binta Hossain and Matthew Dwyer
  5.40
• TransAgent: Enhancing LLM-Based Code Translation via Fine-Grained Execution Alignment (2024)
  Zhiqiang Yuan et al.
  5.35
• DocAgent: A Multi-Agent System for Automated Code Documentation Generation (2025)
  Dayu Yang et al.
  5.35
• Quality In, Quality Out: Investigating Training Data's Role in AI Code Generation (2025)
  Cristina Improta et al.
  5.29
• Unified Modeling Language Code Generation from Diagram Images Using Multimodal Large Language Models (2025)
  Averi Bates et al.
  5.29
• Competitive Programming with Large Reasoning Models (2025)
  OpenAI: Ahmed El-Kishky et al.
  5.24
• 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
• C2SaferRust: Transforming C Projects into Safer Rust with NeuroSymbolic Techniques (2025)
  Vikram Nitin et al.
  5.18
• BitsAI-CR: Automated Code Review via LLM in Practice (2025)
  Tao Sun et al.
  5.18
• On the Effectiveness of LLM-as-a-judge for Code Generation and Summarization (2025)
  Giuseppe Crupi et al.
  5.10
• Towards Translating Real-World Code with LLMs: A Study of Translating to Rust (2024)
  Hasan Ferit Eniser et al.
  5.09
• A Closer Look into Transformer-Based Code Intelligence Through Code Transformation: Challenges and Opportunities (2022)
  Yaoxian Li et al.
  5.06
• KodCode: A Diverse, Challenging, and Verifiable Synthetic Dataset for Coding (2025)
  Zhangchen Xu et al.
  5.04
• CodeContests+: High-Quality Test Case Generation for Competitive Programming (2025)
  Zihan Wang et al.
  5.04
• A Survey on LLM-based Code Generation for Low-Resource and Domain-Specific Programming Languages (2024)
  Sathvik Joel et al.
  5.02
• Willing but Unable: Separating Refusal from Capability in Code LLMs via Abliteration (2026)
  Cristina Carleo et al.
  5.01
• Mutation Without Variation: Convergence Dynamics in LLM-Driven Program Evolution (2026)
  Can Gurkan 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
• SpecGen: Automated Generation of Formal Program Specifications via Large Language Models (2024)
  Lezhi Ma et al.
  4.87
• CodeV: Empowering LLMs with HDL Generation through Multi-Level Summarization (2024)
  Yang Zhao et al.
  4.85
• Optimizing Datasets for Code Summarization: Is Code-Comment Coherence Enough? (2025)
  Antonio Vitale et al.
  4.82
• Improving Deep Assertion Generation via Fine-Tuning Retrieval-Augmented Pre-trained Language Models (2025)
  Quanjun Zhang et al.
  4.82
• Code Summarization Beyond Function Level (2025)
  Vladimir Makharev et al.
  4.82
• Should AI Optimize Your Code? A Comparative Study of Classical Optimizing Compilers Versus Current Large Language Models (2024)
  Miguel Romero Rosas et al.
  4.79
• SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution (2025)
  Chengxing Xie 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
• ALMAS: an Autonomous LLM-based Multi-Agent Software Engineering Framework (2025)
  Vali Tawosi et al.
  4.75
• 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
• A Survey of Neural Code Intelligence: Paradigms, Advances and Beyond (2024)
  Qiushi Sun et al.
  4.63
• Decoding Secret Memorization in Code LLMs Through Token-Level Characterization (2024)
  Yuqing Nie et al.
  4.60
• GeoJSEval: An Automated Evaluation Framework for Large Language Models on JavaScript-Based Geospatial Computation and Visualization Code Generation (2025)
  Guanyu Chen et al.
  4.58