Скачать или смотреть EM-Assist: Safe automated Extract Method refactoring with LLMs

This video accompanies the FSE'24 Tool Demo Submission entitled "EM-Assist: Safe automated ExtractMethod refactoring with LLMs". Excessively long methods, loaded with multiple responsibilities, are challenging to understand, debug, reuse, and maintain. The solution lies in the widely recognized Extract Method refactoring. While the application of this refactoring is supported in modern IDEs,recommending which code fragments to extract has been the topic of many research tools. However, they often struggle to replicate real-world developer practices, resulting in recommendations that do not align with what a human developer would do in real life.

To address this issue, we introduce EM-Assist, an IntelliJ IDEA plugin that uses LLMs to generate refactoring suggestions and subsequently validates, enhances, and ranks them. Finally, EM-Assist uses the IDE to apply the user-selected recommendation.In our extensive evaluation, EM-Assist consistently suggests the correct refactoring among its top-5 recommendations, achieving a60.6% recall rate, surpassing existing tools with a 52.2% recall rate on a synthetic corpus used by other researchers. When replicating 1,615 real-world refactorings that actually took place in open-source projects, EM-Assist’s recall rate was 48.9%, compare dto 23.4% for the previous best-in-class tool that relies solely on static analysis. Moreover, we conducted a usability survey with 18industrial developers and 94.4% gave a positive rating.