Development of a script to aggregate document inspection comments across different platforms to GitHub in a software development PBL

Oh Sato, A. Hazeyama
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Abstract

This study regards inspections conducted in project-based learning (PBL) for software development as learning feedback. To solve the problem that inspection comments are distributed separately across platforms, which is an obstacle to classification of comments, we develop a script, Comment Gatherer, which aggregates inspection comments between GitHub and Figma. Then, we describe the concept of a support application that enables the automatic classification of inspection comments by machine learning.
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在软件开发PBL中开发脚本,将不同平台的文档检查注释聚合到GitHub中
本研究将基于项目的软件开发学习(PBL)中进行的检查视为学习反馈。为了解决检查评论在不同平台上单独分布的问题,这是对评论分类的一个障碍,我们开发了一个脚本,Comment collector,它在GitHub和Figma之间聚合检查评论。然后,我们描述了一个支持应用程序的概念,该应用程序可以通过机器学习对检查评论进行自动分类。
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