mlsanityData to 7 Oct 2026

RepoGraph: Enhancing AI Software Engineering with Repository-level Code Graph

arXiv 2410.14684 ↗First posted 3 Oct 2024cs.SE cs.AI cs.CLcited by 88

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Cited by 51 in LLM agents and tool use, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Large Language Models (LLMs) excel in code generation yet struggle with modern AI software engineering tasks. Unlike traditional function-level or file-level coding tasks, AI software engineering requires not only basic coding proficiency but also advanced skills in managing and interacting with code repositories. However, existing methods often overlook the need for repository-level code understanding, which is crucial for accurately grasping the broader context and developing effective solutions. On this basis, we present RepoGraph, a plug-in module that manages a repository-level structure for modern AI software engineering solutions. RepoGraph offers the desired guidance and serves as a repository-wide navigation for AI software engineers. We evaluate RepoGraph on the SWE-bench by plugging it into four different methods of two lines of approaches, where RepoGraph substantially boosts the performance of all systems, leading to a new state-of-the-art among open-source frameworks. Our analyses also demonstrate the extensibility and flexibility of RepoGraph by testing on another repo-level coding benchmark, CrossCodeEval. Our code is available at https://github.com/ozyyshr/RepoGraph.

Key facts. Cited by 88 papers in the map (data through 7 Oct 2026). Builds on 33 of its 45 references that are in the map. First posted on arXiv 3 Oct 2024.

Builds on

33 of 45 references.

References · 33

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  3. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  4. 2021Program Synthesis with Large Language Modelscited by 3,509
  5. 2023SWE-bench: Can Language Models Resolve Real-World GitHub Issues?cited by 3,193
  6. 2023Code Llama: Open Foundation Models for Codecited by 2,105
  7. 2024SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineeringcited by 1,628
  8. 2024DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligencecited by 1,154
  9. 2024OpenHands: An Open Platform for AI Software Developers as Generalist Agentscited by 956
  10. 2023StarCoder: may the source be with you!cited by 790
  11. 2021CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generationcited by 732
  12. 2024Agentless: Demystifying LLM-based Software Engineering Agentscited by 400
21 more
  1. 2023Large Language Models for Software Engineering: A Systematic Literature Reviewcited by 389
  2. 2023RepoCoder: Repository-Level Code Completion Through Iterative Retrieval and Generationcited by 357
  3. 2024R-Judge: Benchmarking Safety Risk Awareness for LLM Agentscited by 268
  4. 2020Unsupervised Translation of Programming Languagescited by 262
  5. 2023CrossCodeEval: A Diverse and Multilingual Benchmark for Cross-File Code Completioncited by 181
  6. 2023Large Language Models for Software Engineering: Survey and Open Problemscited by 178
  7. 2023CodePlan: Repository-level Coding using LLMs and Planningcited by 139
  8. 2024Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphscited by 116
  9. 2018An Empirical Study on Learning Bug-Fixing Patches in the Wild via Neural Machine Translationcited by 106
  10. 2022Repository-Level Prompt Generation for Large Language Models of Codecited by 106
  11. 2024GRAG: Graph Retrieval-Augmented Generationcited by 77
  12. 2024CodexGraph: Bridging Large Language Models and Code Repositories via Code Graph Databasescited by 62
  13. 2024Alibaba LingmaAgent: Improving Automated Issue Resolution via Comprehensive Repository Explorationcited by 58
  14. 2024Repoformer: Selective Retrieval for Repository-Level Code Completioncited by 55
  15. 2023The Shifted and The Overlooked: A Task-oriented Investigation of User-GPT Interactionscited by 45
  16. 2024Dataflow-Guided Retrieval Augmentation for Repository-Level Code Completioncited by 40
  17. 2024REPOFUSE: Repository-Level Code Completion with Fused Dual Contextcited by 32
  18. 2023Structured Chemistry Reasoning with Large Language Modelscited by 27
  19. 2019CoaCor: Code Annotation for Code Retrieval with Reinforcement Learningcited by 22
  20. 2023Instructed Language Models with Retrievers Are Powerful Entity Linkerscited by 18
  21. 2024Will the Real Linda Please Stand up...to Large Language Models? Examining the Representativeness Heuristic in LLMscited by 12

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 36; 2026: 50.

88 papers.

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  1. 2025Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memorycited by 129
  2. 2025LocAgent: Graph-Guided LLM Agents for Code Localizationcited by 82
  3. 2025Paper2Code: Automating Code Generation from Scientific Papers in Machine Learningcited by 67
  4. 2026A Survey of Agentic Reasoning for Large Language Models: Towards Recursively Self-Improving and Collective Agentscited by 47
  5. 2025UTBoost: Rigorous Evaluation of Coding Agents on SWE-Benchcited by 44
  6. 2025OrcaLoca: An LLM Agent Framework for Software Issue Localizationcited by 43
  7. 2025SWE-QA: Can Language Models Answer Repository-level Code Questions?cited by 37
  8. 2025Code Graph Model (CGM): A Graph-Integrated Large Language Model for Repository-Level Software Engineering Taskscited by 27
  9. 2025PatchPilot: A Cost-Efficient Software Engineering Agent with Early Attempts on Formal Verificationcited by 22
  10. 2025What to Retrieve for Effective Retrieval-Augmented Code Generation? An Empirical Study and Beyondcited by 22
  11. 2025Issue Localization via LLM-Driven Iterative Code Graph Searchingcited by 22
  12. 2025DARS: Dynamic Action Re-Sampling to Enhance Coding Agent Performance by Adaptive Tree Traversalcited by 20
38 more
  1. 2025Retrieval-Augmented Code Generation: A Survey with Focus on Repository-Level Approachescited by 20
  2. 2025Code Researcher: Deep Research Agent for Large Systems Code and Commit Historycited by 19
  3. 2025Improving Code Localization with Repository Memorycited by 19
  4. 2026In Line with Context: Repository-Level Code Generation via Context Inliningcited by 18
  5. 2025How Far Are AI Scientists from Changing the World?cited by 15
  6. 2025An Empirical Study on Failures in Automated Issue Solvingcited by 15
  7. 2025MAPRO: Recasting Multi-Agent Prompt Optimization as Maximum a Posteriori Inferencecited by 15
  8. 2025Co-PatcheR: Collaborative Software Patching with Component(s)-specific Small Reasoning Modelscited by 12
  9. 2025SEAlign: Alignment Training for Software Engineering Agentcited by 11
  10. 2026SGAgent: Suggestion-Guided LLM-Based Multi-Agent Framework for Repository-Level Software Repaircited by 9
  11. 2025Dissecting the SWE-Bench Leaderboards: Profiling Submitters and Architectures of LLM- and Agent-Based Repair Systemscited by 8
  12. 2026SkillRAE: Agent Skill-Based Context Compilation for Retrieval-Augmented Executioncited by 8
  13. 2025RANGER -- Repository-Level Agent for Graph-Enhanced Retrievalcited by 7
  14. 2025InfCode: Adversarial Iterative Refinement of Tests and Patches for Reliable Software Issue Resolutioncited by 7
  15. 2025Agentic Software Issue Resolution with Large Language Models: A Surveycited by 6
  16. 2026Codebase-Memory: Tree-Sitter-Based Knowledge Graphs for LLM Code Exploration via MCPcited by 6
  17. 2026RGFL: Reasoning Guided Fault Localization for Automated Program Repair Using Large Language Modelscited by 5
  18. 2024Context-Augmented Code Generation Using Programming Knowledge Graphscited by 4
  19. 2024Integrating Various Software Artifacts for Better LLM-based Bug Localization and Program Repaircited by 4
  20. 2025Gistify! Codebase-Level Understanding via Runtime Executioncited by 4
  21. 2025GraphLocator: Graph-guided Causal Reasoning for Issue Localizationcited by 4
  22. 2026Repository Intelligence Graph: Deterministic Architectural Map for LLM Code Assistantscited by 4
  23. 2026SWE-Adept: An LLM-Based Agentic Framework for Deep Codebase Analysis and Structured Issue Resolutioncited by 4
  24. 2026REAgent: Requirement-Driven LLM Agents for Software Issue Resolutioncited by 4
  25. 2025Empirical Research on Utilizing LLM-based Agents for Automated Bug Fixing via LangGraphcited by 3
  26. 2025CoRet: Improved Retriever for Code Editingcited by 3
  27. 2025MatchFixAgent: Language-Agnostic Autonomous Repository-Level Code Translation Validation and Repaircited by 3
  28. 2025SpecAgent: A Speculative Retrieval and Forecasting Agent for Code Completioncited by 3
  29. 2025InfCode-C++: Intent-Guided Semantic Retrieval and AST-Structured Search for C++ Issue Resolutioncited by 3
  30. 2026FrogNano: Training a 4B Coding Agent via Online Task Synthesiscited by 3
  31. 2025TENET: One Step Toward Test-Driven Development for Repository-Level Code Generationcited by 2
  32. 2026LIDL: LLM Integration Defect Localization via Knowledge Graph-Enhanced Multi-Agent Analysiscited by 2
  33. 2026ReCodeAgent: A Multi-agent Workflow for Language-Agnostic Translation and Validation of Large-Scale Repositoriescited by 2
  34. 2026ARISE: A Repository-level Graph Representation and Toolset for Agentic Program Repair and Fault Localizationcited by 2
  35. 2026LARGER: Lexically Anchored Repository Graph Exploration and Retrievalcited by 2
  36. 2026Code Isn't Memory: A Structural Codebase Index Inside a Coding Agentcited by 2
  37. 2026What Context Does a Coding Agent Actually Need to Act?cited by 2
  38. 2026GraphIR: Architecture-Level Search States for LLM-Guided Neural Architecture Evolutioncited by 2

50 most cited of 88 All 88 (JSON)