Automatic detection of bad programming habits in scratch: A preliminary study
Automatic detection of bad programming habits in scratch: A preliminary study
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自动检测从头开始的不良编程习惯：初步研究
DOI：
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发表时间：
2014
期刊：
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通讯作者：
G. Robles
中科院分区：
文献类型：
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作者：
J. Moreno;G. Robles
使用 Scratch 环境作为教授编程技能或培养计算思维的工具在各级教育中越来越普遍，从小学到大学都可以找到有据可查的案例研究。然而，有报告显示，在这种环境下学习编程的学生表现出了某些与基本编程建议相悖的习惯。在我们作为高中生指导教师的工作中，我们经常发现这些不良习惯和其他不良习惯，如重复代码和对象命名。本文的重点是通过分析 Scratch 社区网站上的大量项目，验证这些问题是否普遍存在于 Scratch 社区。为了验证这一假设，我们下载了 100 个项目，并使用我们开发的两个插件对其进行分析，以自动检测这些不良做法。这两个插件扩展了 Scratch 项目静态代码分析器 Hairball 工具的功能。结果表明，一般来说，资源库中的项目也会出现所调查的不良行为。除了对未来工作的建议之外，本文还在结论中提出了一些可能有助于解决此类情况的想法。
Using the Scratch environment as a tool to teach programming skills or develop computational thinking is increasingly common in all levels of education, well-documented case studies from primary school to university can be found. However, there are reports that indicate that students learning to program in this environment show certain habits that are contrary to the basic programming recommendations. In our work as instructors with high school students, we have detected these and other bad practices, such as the repetition of code and object naming, on a regular basis. This paper focuses on verifying whether these issues can generally be found in the Scratch community, by analyzing a large number of projects available on the Scratch community website. To test this hypothesis, we downloaded 100 projects and analyzed them with two plug-ins we developed to automatically detect these bad practices. The plug-ins extend the functionality of the Hairball tool, a static code analyzer for Scratch projects. The results obtained show that, in general, projects in the repository also incur in the investigated malpractices. Along with suggestions for future work, some ideas that might assist to address such situations are proposed in the conclusions of the paper.