mlsanityData to 7 Oct 2026

Do Coding Agents Reuse Existing Code or Reinvent the Wheel?

arXiv 2609.35357 ↗First posted 28 Sep 2026cs.SE cs.AI cs.CLcited by 0

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

Abstract (arXiv)

Coding agents are increasingly deployed for iterative development on real repositories, yet existing evaluation barely answers a basic question: do coding agents reuse existing code or reinvent the wheel? The question matters: every duplicated implementation is a fix applied twice and agents produce code far faster than humans can audit, so redundancy accumulates unsupervised. Thus, we present RepoReuse, a multi-turn benchmark for auditing code reuse in real repositories, where requirements are revealed turn by turn and the workspace accumulates across turns. It is built by a fully automated pipeline combining AST-based dependency graphs, guided evidence collection, and execution-verified task synthesis, and scales readily to new repositories. Beyond pass rates, we measure the reuse rate together with recall and cross-turn structural redundancy. An audit over 3,000 turns shows that agents progressively stop exploring relevant repository code, reuse their own history less even when it is fully in the workspace, and leave duplicated logic in 50.8% of task chains by turn~5---all while pass rates barely move. Such deficiencies are invisible to pass rates, underscoring the need to evaluate code generation beyond functional correctness.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 22 of its 36 references that are in the map. First posted on arXiv 28 Sep 2026.

Builds on

22 of 36 references.

Closest ancestors · 8

Same direction, newest first

  1. 2026LoopsBench: From Harness Engineering to Loop Engineering in Coding Agent Evaluation31 Jul
  2. 2026The Scaffold Effect in Coding Agents: Harness Choice as a Hidden Variable in Coding-Agent Evaluation8 Jun
  3. 2026SWE-Explore: Benchmarking How Coding Agents Explore Repositories5 Jun
  4. 2026EvoCode-Bench: Evaluating Coding Agents in Multi-Turn Iterative Interactions22 May
  5. 2026SWE-Chain: Benchmarking Coding Agents on Chained Release-Level Package Upgrades14 May
  6. 2026SlopCodeBench: Benchmarking How Coding Agents Degrade Over Long-Horizon Iterative Tasks25 Mar
  7. 2025SWE-EVO: Benchmarking Coding Agents in Long-Horizon Software Evolution Scenarios20 Dec
  8. 2024Agentless: Demystifying LLM-based Software Engineering Agents1 Jul

Other references · 14

  1. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  2. 2021Program Synthesis with Large Language Modelscited by 3,509
  3. 2023SWE-bench: Can Language Models Resolve Real-World GitHub Issues?cited by 3,193
  4. 2024LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Codecited by 1,906
  5. 2023MemGPT: Towards LLMs as Operating Systemscited by 1,295
  6. 2024A Survey on the Memory Mechanism of Large Language Model based Agentscited by 622
  7. 2023RepoBench: Benchmarking Repository-Level Code Auto-Completion Systemscited by 346
  8. 2025WebSailor: Navigating Super-human Reasoning for Web Agentcited by 218
  9. 2023CrossCodeEval: A Diverse and Multilingual Benchmark for Cross-File Code Completioncited by 181
  10. 2025WebDancer: Towards Autonomous Information Seeking Agencycited by 180
  11. 2025CodeFlowBench: A Multi-turn, Iterative Benchmark for Complex Code Generationcited by 16
  12. 2025MaintainCoder: Maintainable Code Generation Under Dynamic Requirementscited by 13
2 more
  1. 2026DocDancer: Towards Agentic Document-Grounded Information Seekingcited by 11
  2. 2026CiteVQA: Benchmarking Evidence Attribution for Trustworthy Document Intelligencecited by 5

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  1. 2026RefactorPlatform: An Open-Source Harness for Controlled Evaluation of Repository-Scale Refactoring Agents
  2. 2026ReCUBE: Evaluating Repository-Level Context Utilization in Code Generation
  3. 2026VibeMemBench: Evaluating Memory Systems for Coding Agents on Real Repository Coding Tasks
  4. 2026From Dead Code and Static Requirements to Working Engines: Software Revival with Coding Agents
  5. 2026SWE Refactor Bench: Can Coding Agents Complete a Long-Horizon, Whole-Repository Stack Migration?
  6. 2026Self-Evolving Coding Agents
  7. 2026Large-scale Repository Engineering via Agent-Native Reusable Code Primitives
  8. 2025NL2Repo-Bench: Towards Long-Horizon Repository Generation Evaluation of Coding Agents