English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

With the recent advancement of Artificial Intelligence (AI) and LargeLanguage Models (LLMs), AI-based code generation tools become a practicalsolution for software development. GitHub Copilot, the AI pair programmer,utilizes machine learning models trained on a large corpus of code snippets togenerate code suggestions using natural language processing. Despite itspopularity in software development, there is limited empirical evidence on theactual experiences of practitioners who work with Copilot. To this end, weconducted an empirical study to understand the problems that practitioners facewhen using Copilot, as well as their underlying causes and potential solutions.We collected data from 473 GitHub issues, 706 GitHub discussions, and 142 StackOverflow posts. Our results reveal that (1) Operation Issue and CompatibilityIssue are the most common problems faced by Copilot users, (2) Copilot InternalError, Network Connection Error, and Editor/IDE Compatibility Issue areidentified as the most frequent causes, and (3) Bug Fixed by Copilot, ModifyConfiguration/Setting, and Use Suitable Version are the predominant solutions.Based on the results, we discuss the potential areas of Copilot forenhancement, and provide the implications for the Copilot users, the Copilotteam, and researchers.

Exploring the Problems, their Causes and Solutions of AI Pair Programming: A Study on GitHub and Stack Overflow