Key papers

• A Survey on Large Language Models for Code Generation (2024)
  Juyong Jiang et al.
  9.98
• LLMs in Software Security: A Survey of Vulnerability Detection Techniques and Insights (2025)
  Ze Sheng et al.
  7.39
• A Survey on Evaluating Large Language Models in Code Generation Tasks (2024)
  Liguo Chen et al.
  6.08
• Learning Software Bug Reports: A Systematic Literature Review (2025)
  Guoming Long et al.
  5.76
• From Vulnerabilities to Remediation: A Systematic Literature Review of LLMs in Code Security (2024)
  Enna Basic et al.
  5.52
• LLM-Generated Microservice Implementations from RESTful API Definitions (2025)
  Saurabh Chauhan et al.
  5.48
• Agentic Much? Adoption of Coding Agents on GitHub (2026)
  Romain Robbes et al.
  5.19
• A Survey on LLM-based Code Generation for Low-Resource and Domain-Specific Programming Languages (2024)
  Sathvik Joel et al.
  5.02
• Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI (2025)
  Ranjan Sapkota et al.
  4.87
• A Survey of Neural Code Intelligence: Paradigms, Advances and Beyond (2024)
  Qiushi Sun et al.
  4.63
• On the Challenges of Fuzzing Techniques via Large Language Models (2024)
  Linghan Huang et al.
  4.57
• Source Code Summarization in the Era of Large Language Models (2024)
  Weisong Sun and Yun Miao and Yuekang Li and Hongyu Zhang and Chunrong Fang and Yi Liu and Gelei Deng and Yang Liu and Zhenyu Chen
  4.43
• Assessing and Advancing Benchmarks for Evaluating Large Language Models in Software Engineering Tasks (2025)
  Xing Hu et al.
  4.36
• Domain-Driven Design in Practice: A Large-Scale Empirical Characterisation of the Open-Source Ecosystem (2026)
  Ozan \"Ozkan et al.
  4.33
• Industry Classification of GitHub Repositories Using the North American Industry Classification System (NAICS) (2026)
  Kevin Xu et al.
  4.33
• WIP: Software Engineering Competencies in the Age of AI (2026)
  Lynn Vonderhaar et al.
  4.33
• Evaluation Bias and Epistemic Inequality in Global Software Development (2026)
  Sam Khosravi et al.
  4.33
• Instruction-based Image Editing: A Survey on Data, Models, Evaluation, and Applications (2026)
  Xianghao Zang et al.
  4.33
• Beyond the Autoregressive Horizon: A Comprehensive Survey of Diffusion Models, World Modelling, and State Space Models for Code (2026)
  Kishan Maharaj et al.
  4.27
• Usability Analysis of Configurator User Interfaces with Multimodal Large Language Models (2026)
  Sebastian Lubos et al.
  4.22
• Requirements-Driven Automated Software Testing: A Systematic Review (2025)
  Fanyu Wang et al.
  4.19
• A Systematic Literature Review on Explainability for Machine/Deep Learning-based Software Engineering Research (2024)
  Sicong Cao et al.
  4.10
• Intent Formalization: A Grand Challenge for Reliable Coding in the Age of AI Agents (2026)
  Shuvendu K. Lahiri
  3.98
• VerilogDB: The Largest, Highest-Quality Dataset with a Preprocessing Framework for LLM-based RTL Generation (2025)
  Paul E. Calzada et al.
  3.81
• A Survey of LLM-based Automated Program Repair: Taxonomies, Design Paradigms, and Applications (2025)
  Boyang Yang et al.
  3.75
• Exploring the Landscape of Text-to-SQL with Large Language Models: Progresses, Challenges and Opportunities (2025)
  Yiming Huang et al.
  3.70
• Large Language Models for Code Generation: A Comprehensive Survey of Challenges, Techniques, Evaluation, and Applications (2025)
  Nam Huynh and Beiyu Lin
  3.59
• Promptware Engineering: Software Engineering for Prompt-Enabled Systems (2025)
  Zhenpeng Chen et al.
  3.59
• How Are We Doing With Using AI-Based Programming Assistants For Privacy-Related Code Generation? The Developers' Experience (2025)
  Kashumi Madampe et al.
  3.59
• Benchmarking AI Models in Software Engineering: A Review, Search Tool, and Unified Approach for Elevating Benchmark Quality (2025)
  Roham Koohestani et al.
  3.59
• A Taxonomy of Inefficiencies in LLM-Generated Python Code (2025)
  Altaf Allah Abbassi et al.
  3.59
• Automated Non-Functional Requirements Generation in Software Engineering with Large Language Models: A Comparative Study (2025)
  Jomar Thomas Almonte et al.
  3.59
• LawGPT: Knowledge-Guided Data Generation and Its Application to Legal LLM (2025)
  Zhi Zhou et al.
  3.53
• LLMs in Mobile Apps: Practices, Challenges, and Opportunities (2025)
  Kimberly Hau et al.
  3.53
• Towards Advancing Code Generation with Large Language Models: A Research Roadmap (2025)
  Haolin Jin et al.
  3.47
• Self-Improvements in Modern Agentic Systems: A Survey (2026)
  Zhe Ren et al.
  3.45
• A Large-Scale Study of Model Integration in ML-Enabled Software Systems (2024)
  Yorick Sens et al.
  3.31
• From Code Foundation Models to Agents and Applications: A Comprehensive Survey and Practical Guide to Code Intelligence (2025)
  Jian Yang et al.
  3.10
• LLMAID: Identifying AI Capabilities in Android Apps with LLMs (2025)
  Pei Liu et al.
  3.10
• A Survey on Code Generation with LLM-based Agents (2025)
  Yihong Dong et al.
  2.93
• Exploring the Challenges and Opportunities of AI-assisted Codebase Generation (2025)
  Philipp Eibl et al.
  2.93
• A Deep Dive into Retrieval-Augmented Generation for Code Completion: Experience on WeChat (2025)
  Zezhou Yang et al.
  2.87
• Is Safety Standard Same for Everyone? User-Specific Safety Evaluation of Large Language Models (2025)
  Yeonjun In et al.
  2.82
• Build Code Needs Maintenance Too: A Study on Refactoring and Technical Debt in Build Systems (2025)
  Anwar Ghammam et al.
  2.71
• On Developers' Self-Declaration of AI-Generated Code: An Analysis of Practices (2025)
  Syed Mohammad Kashif et al.
  2.71
• Large Language Models for Code Generation: The Practitioners Perspective (2025)
  Zeeshan Rasheed et al.
  2.54
• An Empirical Study on Challenges for LLM Application Developers (2024)
  Xiang Chen et al.
  2.37
• Prompting Techniques for Secure Code Generation: A Systematic Investigation (2024)
  Catherine Tony et al.
  2.32
• Ontology-Amplified Distillation and Contextuality Auditing for Sovereign Enterprise Language Models: A Combined Proof-of-Mechanism and Negative-Results Method Study (2026)
  Thanh Luong Tuan
  1.94
• Evaluating LLM-Generated Code: A Benchmark and Developer Study (2026)
  Joanna Szych and Anne Schwerk
  1.83
• Code as Agent Harness (2026)
  Xuying Ning et al.
  1.83
• Chatbot-Based Assessment of Code Understanding in Automated Programming Assessment Systems (2026)
  Eduard Frankford et al.
  1.78
• Engineering Students' Usage and Perceptions of GitHub Copilot in Open-Source Projects (2026)
  Neha Rani et al.
  1.78
• LLM-Enhanced Log Anomaly Detection: A Comprehensive Benchmark of Large Language Models for Automated System Diagnostics (2026)
  Disha Patel
  1.78
• LLMs Are Not a Silver Bullet: A Case Study on Software Fairness (2026)
  Xinyue Li et al.
  1.78
• Towards Personalizing Secure Programming Education with LLM-Injected Vulnerabilities (2026)
  Matthew Frazier et al.
  1.78
• Prompt-Driven Code Summarization: A Systematic Literature Review (2026)
  Afia Farjana et al.
  1.78
• LLM-Based Multi-Agent Systems for Code Generation: A Multi-Vocal Literature Review (2026)
  Zeeshan Rasheeda et al.
  1.78
• A systematic literature Review for Transformer-based Software Vulnerability detection (2026)
  Fiza Naseer et al.
  1.78
• Sustainable Code Generation Using Large Language Models: A Systematic Literature Review (2026)
  Sabiya Banu Masthan Ali et al.
  1.72