mlsanityData to 7 Oct 2026

ProjectEval: A Benchmark for Programming Agents Automated Evaluation on Project-Level Code Generation

arXiv 2503.07010 ↗First posted 10 Mar 2025cs.SE cs.CLcited by 26

On the map: LLM agents and tool use → Software engineering coding agents

Abstract (arXiv)

Recently, LLM agents have made rapid progress in improving their programming capabilities. However, existing benchmarks lack the ability to automatically evaluate from users' perspective, and also lack the explainability of the results of LLM agents' code generation capabilities. Thus, we introduce ProjectEval, a new benchmark for LLM agents project-level code generation's automated evaluation by simulating user interaction. ProjectEval is constructed by LLM with human reviewing. It has three different level inputs of natural languages or code skeletons. ProjectEval can evaluate the generated projects by user interaction simulation for execution, and by code similarity through existing objective indicators. Through ProjectEval, we find that systematic engineering project code, overall understanding of the project and comprehensive analysis capability are the keys for LLM agents to achieve practical projects. Our findings and benchmark provide valuable insights for developing more effective programming agents that can be deployed in future real-world production.

Key facts. Cited by 26 papers in the map (data through 7 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 28 of its 39 references that are in the map. First posted on arXiv 10 Mar 2025.

Builds on

28 of 39 references.

Closest ancestors · 1

Same direction, newest first

  1. 2023ChatDev: Communicative Agents for Software Development16 Jul

Other references · 27

  1. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  2. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  3. 2021Program Synthesis with Large Language Modelscited by 3,509
  4. 2023SWE-bench: Can Language Models Resolve Real-World GitHub Issues?cited by 3,193
  5. 2023Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generationcited by 1,332
  6. 2021Measuring Coding Challenge Competence With APPScited by 879
  7. 2019CodeSearchNet Challenge: Evaluating the State of Semantic Code Searchcited by 638
  8. 2020Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillationcited by 591
  9. 2020CodeBLEU: a Method for Automatic Evaluation of Code Synthesiscited by 468
  10. 2022DS-1000: A Natural and Reliable Benchmark for Data Science Code Generationcited by 442
  11. 2024CRUXEval: A Benchmark for Code Reasoning, Understanding and Executioncited by 294
  12. 2023ClassEval: A Manually-Crafted Benchmark for Evaluating LLMs on Class-level Code Generationcited by 166
15 more
  1. 2018Learning to Mine Aligned Code and Natural Language Pairs from Stack Overflowcited by 165
  2. 2022Multi-lingual Evaluation of Code Generation Modelscited by 158
  3. 2024Beyond Functional Correctness: Exploring Hallucinations in LLM-Generated Codecited by 106
  4. 2018Mapping Language to Code in Programmatic Contextcited by 104
  5. 2022ReCode: Robustness Evaluation of Code Generation Modelscited by 100
  6. 2024HumanEval-XL: A Multilingual Code Generation Benchmark for Cross-lingual Natural Language Generalizationcited by 84
  7. 2024EvoCodeBench: An Evolving Code Generation Benchmark Aligned with Real-World Code Repositoriescited by 71
  8. 2024EffiBench: Benchmarking the Efficiency of Automatically Generated Codecited by 62
  9. 2024AgileCoder: Dynamic Collaborative Agents for Software Development based on Agile Methodologycited by 45
  10. 2024Prompting Large Language Models to Tackle the Full Software Development Lifecycle: A Case Studycited by 40
  11. 2023CoderEval: A Benchmark of Pragmatic Code Generation with Generative Pre-trained Modelscited by 28
  12. 2024CodeS: Natural Language to Code Repository via Multi-Layer Sketchcited by 28
  13. 2024CodeBenchGen: Creating Scalable Execution-based Code Generation Benchmarkscited by 23
  14. 2022AixBench: A Code Generation Benchmark Datasetcited by 22
  15. 2024Experimenting a New Programming Practice with LLMscited by 17

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 9; 2026: 17.

26 papers.

Sort:

By area:

  1. 2025From LLM Reasoning to Autonomous AI Agents: A Comprehensive Reviewcited by 146
  2. 2026ProgramBench: Can Language Models Rebuild Programs From Scratch?cited by 47
  3. 2025AI Agentic Programming: A Survey of Techniques, Challenges, and Opportunitiescited by 26
  4. 2026SlopCodeBench: Benchmarking How Coding Agents Degrade Over Long-Horizon Iterative Taskscited by 24
  5. 2025Code2Video: A Code-centric Paradigm for Educational Video Generationcited by 23
  6. 2025From Code Foundation Models to Agents and Applications: A Comprehensive Survey and Practical Guide to Code Intelligencecited by 13
  7. 2025Software Development Life Cycle Perspective: A Survey of Benchmarks for Code Large Language Models and Agentscited by 11
  8. 2025Automatically Benchmarking LLM Code Agents through Agent-Driven Annotation and Evaluationcited by 9
  9. 2025Towards Realistic Project-Level Code Generation via Multi-Agent Collaboration and Semantic Architecture Modelingcited by 6
  10. 2025CCFQA: A Benchmark for Cross-Lingual and Cross-Modal Speech and Text Factuality Evaluationcited by 5
  11. 2025Benchmarking and Studying the LLM-based Agent System in End-to-End Software Developmentcited by 5
  12. 2026When the Specification Emerges: Benchmarking Faithfulness Loss in Long-Horizon Coding Agentscited by 5
14 more
  1. 2026JAMER: Project-Level Code Framework Dataset and Benchmark on Professional Game Enginescited by 5
  2. 2026ICAE-Bench: Evaluating Coding Agents as Interactive Project Builderscited by 5
  3. 2026SaaSBench: Exploring the Boundaries of Coding Agents in Long-Horizon Enterprise SaaS Engineeringcited by 3
  4. 2026ASI-Bench: At the Dawn of Artificial Superintelligencecited by 3
  5. 2026Credit-Budgeted ICPC-Style Coding: When Agents Must Pay for Every Decisioncited by 2
  6. 2026LLM-Based Multi-Agent Systems for Code Generation: A Multi-Vocal Literature Reviewcited by 2
  7. 2026PerfCodeBench: Benchmarking LLMs for System-Level High-Performance Code Optimizationcited by 2
  8. 2026RigorBench: Benchmarking Engineering Process Discipline in Autonomous AI Coding Agentscited by 1
  9. 2026From What to How: Bridging User Requirements with Software Development Using Large Language Modelscited by 0
  10. 2026Converted, Not Equivalent: Benchmarking Codebase Conversion via Observational Equivalencecited by 0
  11. 2026LangChoiceBench: Measuring and Explaining Programming-Language Choice in LLMscited by 0
  12. 2026SWE-Game: Can Coding Agents Build the Games We Want?cited by 0
  13. 2026Can Agents Design Libraries for Agents?cited by 0
  14. 2026E2E-SWE: Benchmarking LLMs on Building Working Codebases from Scratchcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025A Survey on Code Generation with LLM-based Agents
  2. 2026ProjDevBench: Benchmarking AI Coding Agents on End-to-End Project Development
  3. 2025Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency
  4. 2026CR-Bench: Evaluating the Real-World Utility of AI Code Review Agents
  5. 2025LoCoBench-Agent: An Interactive Benchmark for LLM Agents in Long-Context Software Engineering
  6. 2026Evaluating LLM Agents on Automated Software Analysis Tasks
  7. 2025AI-Generated Code Is Not Reproducible (Yet): An Empirical Study of Dependency Gaps in LLM-Based Coding Agents
  8. 2026AgentLens: Production-Assessed Trajectory Reviews for Coding Agent Evaluation