一句话：提出 ACE，用经校验的大语言模型重构自动偿还技术债务，提升代码可理解性，缓解开发者的理解瓶颈。
软件系统在 AI 辅助编码下快速膨胀，但软件开发瓶颈已从编写代码转向理解代码；开发者约 70% 时间用于程序理解。ACE 面向这一瓶颈，旨在自动偿还技术债务：借助大语言模型对既有代码实施重构，并对重构结果进行验证，使代码更易理解，从而让有限开发者跟上不断增长的代码库。标题表明其核心是 LLM 驱动的自动化重构与技术债务修复；摘要主要阐述动机，未给出具体验证机制、实验设置、基准或量化效果。
The remarkable advances in AI and Large Language Models (LLMs) have enabled machines to write code, accelerating the growth of software systems. However, the bottleneck in software development is not writing code but understanding it; program understanding is the dominant activity, consuming approximately 70% of developers' time. This implies that improving existing code to make it easier to understand has a high payoff and - in the age of AI-assisted coding - is an essential activity to ensure that a limited pool of developers can keep up with ever-growing codebases.
@inproceedings{paperbot8965,
title = {ACE: Automated Technical Debt Remediation with Validated Large Language Model Refactorings},
author = {Adam Tornhill and Markus Borg and Nadim Hagatulah and Emma Söderberg},
booktitle = {FSE},
year = {2025},
doi = {10.1145/3696630.3730565}
}