@article{10.1145/3661145,
author = {Weber, Thomas and Brandmaier, Maximilian and Schmidt, Albrecht and Mayer, Sven},
title = {Significant Productivity Gains through Programming with Large Language Models},
year = {2024},
issue_date = {June 2024},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {8},
number = {EICS},
url = {https://doi.org/10.1145/3661145},
doi = {10.1145/3661145},
abstract = {Large language models like GPT and Codex drastically alter many daily tasks, including programming, where they can rapidly generate code from natural language or informal specifications. Thus, they will change what it means to be a programmer and how programmers act during software development. This work explores how AI assistance for code generation impacts productivity. In our user study (N=24), we asked programmers to complete Python programming tasks supported by a) an auto-complete interface using GitHub Copilot, b) a conversational system using GPT-3, and c) traditionally with just the web browser. Aside from significantly increasing productivity metrics, participants displayed distinctive usage patterns and strategies, highlighting that the form of presentation and interaction affects how users engage with these systems. Our findings emphasize the benefits of AI-assisted coding and highlight the different design challenges for these systems.},
journal = {Proc. ACM Hum.-Comput. Interact.},
month = {jun},
articleno = {256},
numpages = {29},
keywords = {github copilot, gpt, language models, programming, software development, user study}
}