Catching Developers in the Flow: Low-Latency Agentic Program Repair at Google Scale
Manual repair of program failures is time-consuming and disruptive for software developers, particularly during the pre-submit phase where test failures occur within continuous integration systems. While Automated Program Repair has seen significant advancement through Large Language Models, existing state-of-the-art techniques primarily focus on post-submit workflows, operating offline without the low-latency requirements necessary to assist developers in real-time within their flow before they switch context. In this paper, we introduce FlowAgent, an AI agent deployed at Google to automatically repair test failures in the pre-submit outer-loop workflow inside continuous integration syst...
| Authors | Celal Ziftci, Spencer Greene, Ray Liu et al. |
|---|---|
| Primary category | cs.SE |
| Published | 5 October 2026 |
| Last updated at source | 5 October 2026 |
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