SWE-Journey: Towards More Realistic Evaluation of Coding Assistants through Long-Horizon, Multi-Turn Interaction
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Computer Science > Computation and Language
arXiv:2610.11559 (cs)
[Submitted on 8 Oct 2026]
Title:SWE-Journey: Towards More Realistic Evaluation of Coding Assistants through Long-Horizon, Multi-Turn Interaction
Authors:Hexuan Deng, Yue Wang, Wenyu Jiang, Cheng Yang, Haolin Yang, Zhaohua Zhang, Chenchen Zhao, Beiduo Chen, Muxi Chen, Sa Zhu, Geyuan Zhu, Jianhuan Zhuo, Qiuyong Xiao, Tianwen Jiang, Jihong Zhang, Xuebo Liu
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Abstract:Coding assistants such as Claude Code and Codex have become a major application of LLM agents, yet existing benchmarks remain far from real-world use, particularly in task horizon and interaction length. Code assistants require completing long chains of development work in continuously evolving repositories, while repeatedly clarifying requirements and adapting implementations through multi-turn interaction. To address these gaps, we introduce SWE-Journey, a benchmark for more realistic evaluation of coding assistants. To address the task-horizon gap, we propose a weak-to-strong synthesis pipeline that automatically constructs long-horizon coding tasks. To address the interaction gap, we mine four representative user personas from real interaction data and build a user-simulation agent to reproduce realistic code-assistance interactions. On average, models pass over 75% of tests for requested functionality with software architects, but fewer than 25% with non-coders. These results show that current coding assistants still fall short of enabling reliable coding for non-coders. We further analyze the reasons for this gap and identify asking right, finding right, and fixing right as key capabilities during interaction.
| Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Multiagent Systems (cs.MA); Software Engineering (cs.SE) |
| Cite as: | arXiv:2610.11559 [cs.CL] |
| (or arXiv:2610.11559v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2610.11559
arXiv-issued DOI via DataCite (pending registration)
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View a PDF of the paper titled SWE-Journey: Towards More Realistic Evaluation of Coding Assistants through Long-Horizon, Multi-Turn Interaction, by Hexuan Deng and 15 other authors
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