How Scientists Use Large Language Models to Program

要旨

Scientists across disciplines write code for critical activities like data collection and generation, statistical modeling, and visualization. As large language models that can generate code have become widely available, scientists may increasingly use these models during research software development. We investigate the characteristics of scientists who are early-adopters of code generating models and conduct interviews with scientists at a public, research-focused university. Through interviews and reviews of user interaction logs, we see that scientists often use code generating models as an information retrieval tool for navigating unfamiliar programming languages and libraries. We present findings about their verification strategies and discuss potential vulnerabilities that may emerge from code generation practices unknowingly influencing the parameters of scientific analyses.

著者
Gabrielle O'Brien
University of Michigan, Ann Arbor, Michigan, United States
DOI

10.1145/3706598.3713668

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713668

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Programming and Interaction

G304
7 件の発表
2025-05-01 18:00:00
2025-05-01 19:30:00
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