arxiv:2601.21102

The Quiet Contributions: Insights into AI-Generated Silent Pull Requests

Published on Jan 28

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Abstract

Researchers conducted an empirical analysis of silent AI-generated pull requests to understand their impact on code quality and security, examining 4,762 examples from popular Python repositories.

AI-generated summary

We present the first empirical study of AI-generated pull requests that are 'silent,' meaning no comments or discussions accompany them. This absence of any comments or discussions associated with such silent AI pull requests (SPRs) poses a unique challenge in understanding the rationale for their acceptance or rejection. Hence, we quantitatively study 4,762 SPRs of five AI agents made to popular Python repositories drawn from the AIDev public dataset. We examine SPRs impact on code complexity, other quality issues, and security vulnerabilities, especially to determine whether these insights can hint at the rationale for acceptance or rejection of SPRs.

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