VQV Signal
Research shows that generate-test-revise loops in coding agents do not guarantee reliability, with correctness dropping after multiple revisions. A study of 900 revision trajectories reveals a decline in current correctness from 82% after one revision to 67.3% after two.
Research shows that generate-test-revise loops in coding agents do not guarantee reliability, with correctness dropping after multiple revisions. A study of 900 revision trajectories reveals a decline in current correctness from 82% after one revision to 67.3% after two.
AI-assisted summary based on the listed source.
Generate--test--revise loops are common in coding agents, but repetition alone provides no reliability guarantee. We study the gap between finding a correct patch and retaining, verifying, and submitting it. A sealed five-seed study over 30 HumanEval repairs produces 900 three-revision trajectories. Under forced...
This highlights a critical gap between finding a correct code patch and maintaining its correctness through revisions, impacting the trustworthiness of AI-assisted code repair. Understanding these limitations is essential for improving agentic code repair systems.
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VQV surfaced this signal because it is recent, relevant to AI Coding Tools, connected to arXiv.
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