RepoLaunch: Automating Build and Management of Code Repositories across Languages and Platforms

RepoLaunch automates cross-language repository builds and testing, achieving 78% build success and enabling fully automated SWE dataset pipelines.

Kenan Li, Rongzhi Li, Linghao Zhang, Qirui Jin, Liao Zhu, XiaoSong Huang, Geng Zhang, Yikai Zhang, Shilin He, Chengxing Xie, Xin Zhang, Zijian Jin, Bowen Li, Chaoyun Zhang, Yu Kang, Yufan Huang, Elsie Nallipogu, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang

Published 2026Atlanta Poster Session 4 · Thu, Dec 10, 4:30 PM–7:30 PM local time · Hall C1arXiv ↗OpenReview ↗

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Abstract

Language model (LM) agents have driven substantial progress in automated software engineering (SWE), yet building and testing software repositories at scale remains a largely manual and labor-intensive bottleneck. In this work, we introduce RepoLaunch, a novel agentic framework that automatically resolves dependencies, compiles source code, and extracts test results across diverse programming languages and operating systems. RepoLaunch achieves a 78% build success rate, outperforming the Python/Linux-only prior system by 18%. To demonstrate its application, we further present a fully automated pipeline for SWE dataset creation driven by RepoLaunch, which only requires human input at the task-design stage. RepoLaunch is open-sourced, and its automated task-generation pipeline has already been adopted by several recent works on agentic benchmarking and training.