An abstract method linearization for detecting source code plagiarism in object-oriented environment

Oscar Karnalim
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引用次数: 11

Abstract

Despite the fact that plagiarizing source code is a trivial task for most CS students, detecting such unethical behavior requires a considerable amount of effort. Thus, several plagiarism detection systems were developed to handle such issue. This paper extends Karnalim's work, a low-level approach for detecting Java source code plagiarism, by incorporating abstract method linearization. Such extension is incorporated to enhance the accuracy of low-level approach in term of detecting plagiarism in object-oriented environment. According to our evaluation, which was conducted based on 23 design-pattern source code pairs, our extended low-level approach is more effective than state-of-the-art and Karnalim's approach. On the one hand, when compared to state-of-the-art approach, our approach can generate less coincidental similarities and provide more accurate result. On the other hand, when compared to Karnalim's approach, our approach, at some extent, can generate higher similarity when simple abstract method invocation is incorporated.
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面向对象环境下源代码抄袭检测的抽象线性化方法
尽管抄袭源代码对大多数计算机科学专业的学生来说是一件微不足道的事情,但检测这种不道德的行为需要付出相当大的努力。因此,开发了几个剽窃检测系统来处理这一问题。本文扩展了Karnalim的工作,这是一种检测Java源代码抄袭的低级方法,通过合并抽象方法线性化。为了提高底层方法在面向对象环境下抄袭检测的准确性,引入了这种扩展。根据我们基于23个设计模式源代码对进行的评估,我们扩展的低级方法比最先进的方法和Karnalim的方法更有效。一方面,与最先进的方法相比,我们的方法可以产生更少的巧合相似点,提供更准确的结果。另一方面,与Karnalim的方法相比,我们的方法在某种程度上可以在合并简单抽象方法调用时产生更高的相似性。
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