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With the recent advancement of Artificial Intelligence (AI) and the emergenceof Large Language Models (LLMs), AI-based code generation tools have achievedsignificant progress and become a practical solution for software development.GitHub Copilot, referred to as AI pair programmer, utilizes machine learningmodels that are trained on a large corpus of code snippets to generate codesuggestions or auto-complete code using natural language processing. Despiteits popularity, there is little empirical evidence on the actual experiences ofsoftware developers who work with Copilot. To this end, we conducted anempirical study to understand the issues and challenges that developers facewhen using Copilot in practice, as well as their underlying causes andpotential solutions. We collected data from 476 GitHub issues, 706 GitHubdiscussions, and 184 Stack Overflow posts, and identified the issues, causesthat trigger the issues, and solutions that resolve the issues when usingCopilot. Our results reveal that (1) Usage Issue and Compatibility Issue arethe most common problems faced by Copilot users, (2) Copilot Internal Issue,Network Connection Issue, and Editor/IDE Compatibility Issue are identified asthe most frequent causes, and (3) Bug Fixed by Copilot, ModifyConfiguration/Setting, and Use Suitable Version are the predominant solutions.Based on the results, we delve into the main challenges users encounter whenimplementing Copilot in practical development, the possible impact of Copiloton the coding process, aspects in which Copilot can be further enhanced, andpotential new features desired by Copilot users.

On the Concerns of Developers When Using GitHub Copilot