一句话：分析 JetBrains Academy 超百万 Java/Python 提交，揭示代码质量问题类型、修复动态及课程改进方向。
在线编程课程中学生代码质量难以控制。本文分析 JetBrains Academy 平台上逾 100 万份 Java 和 130 万份 Python 提交，该平台嵌入 Hyperstyle 代码质量评估工具。作者考察最常见代码质量问题类型、学生修复这些问题的动态，并对若干问题开展案例研究，分析即使多次尝试仍未被修复的原因；还研究学生通过任务后仍异常长地提交以修复质量问题的序列。结果可为改进在线课程提供依据，例如避免任务设计激励学生写出低质量代码。
Programming education should aim to provide students with a broad range of skills that they will later use while developing software. An important aspect in this is their ability to write code that is not only correct but also of high quality. Unfortunately, this is difficult to control in the setting of a massive open online course. In this paper, we carry out an analysis of the code quality of submissions from JetBrains Academy — a platform for studying programming in an industry-like project-based setting with an embedded code quality assessment tool called Hyperstyle. We analyzed more than a million Java submissions and more than 1.3 million Python submissions, studied the most prevalent types of code quality issues and the dynamics of how students fix them. We provide several case studies of different issues, as well as an analysis of why certain issues remain unfixed even after several attempts. Also, we studied abnormally long sequences of submissions, in which students attempted to fix code quality issues after passing the task. Our results point the way towards the improvement of online courses, such as making sure that the task itself does not incentivize students to write code poorly.
DOI 原文 · arXiv · PDF（开放获取） · DBLP
@inproceedings{abs-2301-11158,
title = {Analyzing the Quality of Submissions in Online Programming Courses},
author = {Maria Tigina and Anastasiia Birillo and Yaroslav Golubev and Hieke Keuning and Nikolay Vyahhi and Timofey Bryksin},
booktitle = {ICSE},
year = {2023},
doi = {10.1109/icse-seet58685.2023.00031}
}