Environment-in-the-Loop: Rethinking Code Migration with LLM-based Agents
Xiang Li, Zhiwei Fei, Ying Ma, Jerry Zhang, Sarro Federica, He Ye

TL;DR
This paper highlights the importance of integrating environment interaction with code migration using LLMs, proposing a new framework to improve automation and reduce rework in software evolution.
Contribution
It introduces a novel framework that combines environment setup with code migration, addressing a gap in current automated code migration approaches.
Findings
Automated environment interaction is crucial for effective code migration.
Current static analysis methods are insufficient for understanding target environments.
Integrating environment setup can significantly reduce rework and project delays.
Abstract
Modern software systems continuously undergo code upgrades to enhance functionality, security, and performance, and Large Language Models (LLMs) have demonstrated remarkable capabilities in code migration tasks. However, while research on automated code migration which including refactoring, API adaptation, and dependency updates has advanced rapidly, the exploration of the automated environment interaction that must accompany it remains relatively scarce. In practice, code and its environment are intricately intertwined. Relying solely on static analysis of the environment leads to an inadequate understanding of the target setting, prolongs feedback cycles, and consequently causes significant rework and project delays, thereby reducing overall efficiency. We contend that successful software evolution demands a holistic perspective that integrates both code and environment migration. To…
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Taxonomy
TopicsSoftware Engineering Research · Software System Performance and Reliability · Advanced Software Engineering Methodologies
