Arrow Research search
Back to NeurIPS

NeurIPS 2024

SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering

Conference Paper Main Conference Track Artificial Intelligence ยท Machine Learning

Abstract

Language model agents are increasingly being used to automate complicated tasks in digital environments. Just as humans benefit from powerful software applications, such as integrated development environments, for complex tasks like software engineering, we posit that language model agents represent a new category of end users with their own needs and abilities, and would benefit from specially built interfaces to the software they use. We investigate how the role of interface design affects the performance of language model agents. As a result of this exploration, we introduce SWE-agent: a system that facilitates language model agents to autonomously use computers to solve software engineering tasks. SWE-agent's custom agent-computer interface significantly enhances an agent's ability to create and edit code files, navigate entire repositories, and execute tests and other programs. We evaluate SWE-agent on SWE-bench and HumanEvalFix, achieving state-of-the-art performance on both with a pass@1 rate of 12. 5% and 87. 7%, respectively, far exceeding the previous state-of-the-art achieved with non-interactive language models. Finally, we provide insight on how the design of the agent-computer interface can impact agents' behavior and performance.

Authors

Keywords

No keywords are indexed for this paper.

Context

Venue
Annual Conference on Neural Information Processing Systems
Archive span
1987-2025
Indexed papers
30776
Paper id
608518858465944726