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A methodology to teach exemplary coding style considering students' coding style feature contains fluctuations

机译:考虑学生编码风格特征的教学示例编码风格的方法包含波动

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Readable source code should contain a relatively small amount of latent bugs and should be easy to maintain. However, it is difficult for a teacher to teach all students to write code in accordance with a certain coding style because each of them naturally has his/her own different coding styles, and the teacher needs to advise them considering their original coding styles. To deal with this issue, the CM algorithm is introduced, which was originally developed to detect source code plagiarism in Java programming classes. It quantifies a student's coding style feature by using a set of hidden Markov models called coding models. Coding models quantify a person's code writing style as that person's coding style feature. In this paper, an attempt to apply the CM algorithm for facilitating coding style instruction is reported. Experimental results showed that the coding models provided information that was useful for teaching coding styles.
机译:可读的源代码应包含相对较少的潜在错误,并且应易于维护。但是,老师很难教导所有学生按照某种编码风格编写代码,因为他们每个人自然都有自己不同的编码风格,并且老师需要建议他们考虑自己的原始编码风格。为了解决这个问题,引入了CM算法,该算法最初是为了检测Java编程类中的源代码抄袭而开发的。它通过使用一组称为编码模型的隐马尔可夫模型来量化学生的编码风格特征。编码模型将一个人的编码写作风格量化为该人的编码风格特征。在本文中,报告了尝试将CM算法用于促进编码风格指令的尝试。实验结果表明,编码模型提供了可用于教授编码样式的信息。

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