SWE-Hub: A Unified Production System for Scalable, Executable Software Engineering Tasks
Yucheng Zeng, Shupeng Li, Daxiang Dong, Ruijie Xu, Zimo Chen, Liwei Zheng, Yuxuan Li, Zhe Zhou, Haotian Zhao, Lun Tian, Heng Xiao, Tianshu Zhu, Longkun Hao, Jianmin Wu

TL;DR
SWE-Hub is a comprehensive system that automates environment setup, scalable bug synthesis, and task generation to produce realistic, executable software engineering data for training and evaluation.
Contribution
It introduces a unified pipeline combining environment automation, scalable bug synthesis, and task creation, addressing key challenges in generating realistic software engineering data.
Findings
Automates environment creation across multiple languages.
Synthesizes large volumes of bug-fix instances efficiently.
Generates diverse repair and creation tasks from natural language.
Abstract
Progress in software-engineering agents is increasingly constrained by the scarcity of executable, scalable, and realistic data for training and evaluation. This scarcity stems from three fundamental challenges in existing pipelines: environments are brittle and difficult to reproduce across languages; synthesizing realistic, system-level bugs at scale is computationally expensive; and existing data predominantly consists of short-horizon repairs, failing to capture long-horizon competencies like architectural consistency. We introduce \textbf{SWE-Hub}, an end-to-end system that operationalizes the data factory abstraction by unifying environment automation, scalable synthesis, and diverse task generation into a coherent production stack. At its foundation, the \textbf{Env Agent} establishes a shared execution substrate by automatically converting raw repository snapshots into…
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Taxonomy
TopicsSoftware Engineering Research · Software Testing and Debugging Techniques · Advanced Software Engineering Methodologies
