Co-Modifying Application Code and Deployment Infrastructure: A Causal Study of AI Agent Pull Requests
Because agents lack deployment awareness, attempting cross-domain modifications introduces unverified dependencies into asynchronous integration pipelines.
ProofPaper ↗
Key points
- Current software engineering agents are evaluated predominantly inside isolated sandboxes against synchronous local tests.
- However, deploying features in collaborative repositories requires modifying continuous integration (CI/CD) pipelines, containers, and provisioning manifests alongside application logic.
- To isolate the causal integration overhead of dual-scope pull requests (PRs)-modifying both application code and deployment infrastructure-we evaluated 26,999 PRs across two large datasets (AIDev v5 and MOSAIC-3M) encompassing six agent architectures and an aligned human baseline.
- Using a deterministic four-tier file taxonomy and an exact 4D strata-matching framework, we isolated integration metrics under conditional exchangeability while controlling for application volume.
Sources (1)
- [1]Co-Modifying Application Code and Deployment Infrastructure: A Causal Study of AI Agent Pull RequestsarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 9, 01:16 AM
Because agents lack deployment awareness, attempting cross-domain modifications introduces unverified dependencies into asynchronous integration pipelines.
Current software engineering agents are evaluated predominantly inside isolated sandboxes against synchronous local tests.
Extractive summary: sentences quoted from the sources.
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