A Study of Library Usage in Agent-Authored Pull Requests

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Twist, Lukas, Zhang, Jie M.
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866911401116696576
author Twist, Lukas
Zhang, Jie M.
author_facet Twist, Lukas
Zhang, Jie M.
contents Coding agents are becoming increasingly capable of completing end-to-end software engineering workflows that previously required a human developer, including raising pull requests (PRs) to propose their changes. However, we still know little about how these agents use libraries when generating code, a core part of real-world software development. To fill this gap, we study 26,760 agent-authored PRs from the AIDev dataset to examine three questions: how often do agents import libraries, how often do they introduce new dependencies (and with what versioning), and which specific libraries do they choose? We find that agents often import libraries (29.5% of PRs) but rarely add new dependencies (1.3% of PRs); and when they do, they follow strong versioning practices (75.0% specify a version), an improvement on direct LLM usage where versions are rarely mentioned. Generally, agents draw from a surprisingly diverse set of external libraries, contrasting with the limited "library preferences" seen in prior non-agentic LLM studies. Our findings offer an early empirical view on how AI coding agents interact with today's software ecosystems.
format Preprint
id arxiv_https___arxiv_org_abs_2512_11589
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Study of Library Usage in Agent-Authored Pull Requests
Twist, Lukas
Zhang, Jie M.
Software Engineering
Coding agents are becoming increasingly capable of completing end-to-end software engineering workflows that previously required a human developer, including raising pull requests (PRs) to propose their changes. However, we still know little about how these agents use libraries when generating code, a core part of real-world software development. To fill this gap, we study 26,760 agent-authored PRs from the AIDev dataset to examine three questions: how often do agents import libraries, how often do they introduce new dependencies (and with what versioning), and which specific libraries do they choose? We find that agents often import libraries (29.5% of PRs) but rarely add new dependencies (1.3% of PRs); and when they do, they follow strong versioning practices (75.0% specify a version), an improvement on direct LLM usage where versions are rarely mentioned. Generally, agents draw from a surprisingly diverse set of external libraries, contrasting with the limited "library preferences" seen in prior non-agentic LLM studies. Our findings offer an early empirical view on how AI coding agents interact with today's software ecosystems.
title A Study of Library Usage in Agent-Authored Pull Requests
topic Software Engineering
url https://arxiv.org/abs/2512.11589