mlsanityData to 7 Oct 2026

LLM-Based Agentic Systems for Software Engineering: Challenges and Opportunities

arXiv 2601.09822 ↗First posted 14 Jan 2026cs.SE cs.AIcited by 7

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

Abstract (arXiv)

Despite recent advancements in Large Language Models (LLMs), complex Software Engineering (SE) tasks require more collaborative and specialized approaches. This concept paper systematically reviews the emerging paradigm of LLM-based multi-agent systems, examining their applications across the Software Development Life Cycle (SDLC), from requirements engineering and code generation to static code checking, testing, and debugging. We delve into a wide range of topics such as language model selection, SE evaluation benchmarks, state-of-the-art agentic frameworks and communication protocols. Furthermore, we identify key challenges and outline future research opportunities, with a focus on multi-agent orchestration, human-agent coordination, computational cost optimization, and effective data collection. This work aims to provide researchers and practitioners with valuable insights into the current forefront landscape of agentic systems within the software engineering domain.

Key facts. Cited by 7 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 48 of its 64 references that are in the map. First posted on arXiv 14 Jan 2026.

Builds on

48 of 64 references.

Closest ancestors · 4

Same direction, newest first

  1. 2024MARE: Multi-Agents Collaboration Framework for Requirements Engineering6 May
  2. 2024CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challenges14 Jan
  3. 2023Static Code Analysis in the AI Era: An In-depth Exploration of the Concept, Function, and Potential of Intelligent Code Analysis Agents13 Oct
  4. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation16 Aug

Other references · 44

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2021Training Verifiers to Solve Math Word Problemscited by 9,743
  4. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  5. 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,064
  6. 2023A Survey of Large Language Modelscited by 2,537
  7. 2022Emergent Abilities of Large Language Modelscited by 2,483
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  9. 2023CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Societycited by 1,348
  10. 2023Teaching Large Language Models to Self-Debugcited by 963
  11. 2024Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Surveycited by 641
  12. 2024A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applicationscited by 428
32 more
  1. 2023MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedbackcited by 293
  2. 2023InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedbackcited by 229
  3. 2023An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generationcited by 193
  4. 2023CodePlan: Repository-level Coding using LLMs and Planningcited by 139
  5. 2023Keep the Conversation Going: Fixing 162 out of 337 bugs for 0.42 each using ChatGPTcited by 125
  6. 2023No More Manual Tests? Evaluating and Improving ChatGPT for Unit Test Generationcited by 82
  7. 2025A Survey of AI Agent Protocolscited by 77
  8. 2022Parsel: Algorithmic Reasoning with Language Models by Composing Decompositionscited by 62
  9. 2023CodeChain: Towards Modular Code Generation Through Chain of Self-revisions with Representative Sub-modulescited by 58
  10. 2024SpecGen: Automated Generation of Formal Program Specifications via Large Language Modelscited by 51
  11. 2023Large Language Model-Powered Smart Contract Vulnerability Detection: New Perspectivescited by 48
  12. 2024AgentFL: Scaling LLM-based Fault Localization to Project-Level Contextcited by 47
  13. 2023SelfEvolve: A Code Evolution Framework via Large Language Modelscited by 43
  14. 2023Make LLM a Testing Expert: Bringing Human-like Interaction to Mobile GUI Testing via Functionality-aware Decisionscited by 41
  15. 2023Explainable Automated Debugging via Large Language Model-driven Scientific Debuggingcited by 40
  16. 2023Prompting Is All You Need: Automated Android Bug Replay with Large Language Modelscited by 40
  17. 2023ToolCoder: Teach Code Generation Models to use API search toolscited by 37
  18. 2023ClarifyGPT: Empowering LLM-based Code Generation with Intention Clarificationcited by 37
  19. 2023WhiteFox: White-Box Compiler Fuzzing Empowered by Large Language Modelscited by 37
  20. 2024Teaching Code LLMs to Use Autocompletion Tools in Repository-Level Code Generationcited by 30
  21. 2023CodeCoT: Tackling Code Syntax Errors in CoT Reasoning for Code Generationcited by 29
  22. 2024A Pair Programming Framework for Code Generation via Multi-Plan Exploration and Feedback-Driven Refinementcited by 21
  23. 2024Multi-role Consensus through LLMs Discussions for Vulnerability Detectioncited by 19
  24. 2023INTERVENOR: Prompting the Coding Ability of Large Language Models with the Interactive Chain of Repaircited by 18
  25. 2025Agentic AI Frameworks: Architectures, Protocols, and Design Challengescited by 16
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  29. 2024FsPONER: Few-shot Prompt Optimization for Named Entity Recognition in Domain-specific Scenarioscited by 6
  30. 2025Bridging the Prototype-Production Gap: A Multi-Agent System for Notebooks Transformationcited by 6
  31. 2023Tests4Py: A Benchmark for System Testingcited by 2
  32. 2024Conceptual In-Context Learning and Chain of Concepts: Solving Complex Conceptual Problems Using Large Language Modelscited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 7.

7 papers.

  1. 2026Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systemscited by 5
  2. 2026PerfCodeBench: Benchmarking LLMs for System-Level High-Performance Code Optimizationcited by 2
  3. 2026Agent4cs: A Multi-agent System for Code Summarization in Large Hierarchical Codebasescited by 1
  4. 2026OneDayAgent: Towards a Long-Horizon Harness for Autonomous Agentscited by 1
  5. 2026Code Broker: A Multi-Agent System for Automated Code Quality Assessmentcited by 0
  6. 2026PromptMN: Pseudo Prompting Languagecited by 0
  7. 2026Agent4RE: A Self-Refining Multi-agent Framework for End-to-End Software Requirements Engineering and Benchmarkingcited by 0

Similar, not cited

Close in wording, no citation either way

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  3. 2026Developing LLM-based Multi-Agent Systems in Software Engineering: A Mixed-Method Experience Report
  4. 2025Designing LLM-based Multi-Agent Systems for Software Engineering Tasks: Quality Attributes, Design Patterns and Rationale
  5. 2025A Comprehensive Survey on Benchmarks and Solutions in Software Engineering of LLM-Empowered Agentic System
  6. 2024From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Future
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  8. 2025ALMAS: an Autonomous LLM-based Multi-Agent Software Engineering Framework