How to Refactor this Code? An Exploratory Study on Developer-ChatGPT Refactoring Conversations

Large Language Models (LLMs), like ChatGPT, have gained widespread popularity and usage in various software engineering tasks, including refactoring, testing, code review, and program comprehension. Despite recent studies delving into refactoring documentation in commit messages, issues, and code re...

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Published in:Proceedings (IEEE/ACM International Conference on Mining Software Repositories. Online) pp. 202 - 206
Main Authors: AlOmar, Eman Abdullah, Venkatakrishnan, Anushkrishna, Mkaouer, Mohamed Wiem, Newman, Christian D., Ouni, Ali
Format: Conference Proceeding
Language:English
Published: ACM 15.04.2024
Subjects:
Chatbots
ChatGPT
Codes
Documentation
mining software repositories
Oral communication
Refactoring documentation
Reviews
Software quality
Text mining
ISSN:2574-3864
Online Access:Get full text
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Abstract Large Language Models (LLMs), like ChatGPT, have gained widespread popularity and usage in various software engineering tasks, including refactoring, testing, code review, and program comprehension. Despite recent studies delving into refactoring documentation in commit messages, issues, and code review, little is known about how developers articulate their refactoring needs when interacting with ChatGPT. In this paper, our goal is to explore conversations between developers and ChatGPT related to refactoring to better understand how developers identify areas for improvement in code and how ChatGPT addresses developers' needs. Our approach relies on text mining refactoring-related conversations from 17,913 ChatGPT prompts and responses, and investigating developers' explicit refactoring intention. Our results reveal that (1) developer-ChatGPT conversations commonly involve generic and specific terms/phrases; (2) developers often make generic refactoring requests, while ChatGPT typically includes the refactoring intention; and (3) various learning settings when prompting ChatGPT in the context of refactoring. We envision that our findings contribute to a broader understanding of the collaboration between developers and AI models.CCS CONCEPTS* Software Engineering → Software Quality; Refactoring.
AbstractList Large Language Models (LLMs), like ChatGPT, have gained widespread popularity and usage in various software engineering tasks, including refactoring, testing, code review, and program comprehension. Despite recent studies delving into refactoring documentation in commit messages, issues, and code review, little is known about how developers articulate their refactoring needs when interacting with ChatGPT. In this paper, our goal is to explore conversations between developers and ChatGPT related to refactoring to better understand how developers identify areas for improvement in code and how ChatGPT addresses developers' needs. Our approach relies on text mining refactoring-related conversations from 17,913 ChatGPT prompts and responses, and investigating developers' explicit refactoring intention. Our results reveal that (1) developer-ChatGPT conversations commonly involve generic and specific terms/phrases; (2) developers often make generic refactoring requests, while ChatGPT typically includes the refactoring intention; and (3) various learning settings when prompting ChatGPT in the context of refactoring. We envision that our findings contribute to a broader understanding of the collaboration between developers and AI models.CCS CONCEPTS* Software Engineering → Software Quality; Refactoring.
Author AlOmar, Eman Abdullah
Newman, Christian D.
Ouni, Ali
Venkatakrishnan, Anushkrishna
Mkaouer, Mohamed Wiem
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  organization: University of Quebec,ETS Montreal,Montreal,Quebec,Canada
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Snippet Large Language Models (LLMs), like ChatGPT, have gained widespread popularity and usage in various software engineering tasks, including refactoring, testing,...
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StartPage 202
SubjectTerms Chatbots
ChatGPT
Codes
Documentation
mining software repositories
Oral communication
Refactoring documentation
Reviews
Software quality
Text mining
Title How to Refactor this Code? An Exploratory Study on Developer-ChatGPT Refactoring Conversations
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