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  "text": "NEW Research from Google.\n\nIntegration test failures are painful because the signal is buried in messy logs. Massive output, heterogeneous systems, low signal-to-noise ratio, and unclear root causes.\n\nThis paper introduces Auto-Diagnose, an LLM-based tool deployed inside Google's Critique code review system.\n\nAuto-Diagnose analyzes failure logs, summarizes the most relevant lines, and suggests the root cause in the developer workflow where the failure is already being reviewed.\n\nThe deployment numbers are notable. In a manual evaluation of 71 real-world failures, Auto-Diagnose reached 90.14% root-cause diagnosis accuracy.\n\nAfter Google-wide deployment, it was used across 52,635 distinct failing tests. User feedback marked it \"Not helpful\" in only 5.8% of cases, and it ranked #14 in helpfulness among 370 Critique tools.\n\nPaper: https://t.co/KJq3LgETpa\n\nLearn to build effective AI agents in our academy: https://t.co/1e8RZKs4uX",
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