An Abstract Method Linearization for Detecting Source Code Plagiarism in Object-Oriented Environment

TL;DR

This paper enhances a low-level Java source code plagiarism detection method by incorporating abstract method linearization, resulting in improved accuracy and fewer false positives in object-oriented environments.

Contribution

It introduces abstract method linearization into Karnalim's low-level approach, significantly improving plagiarism detection accuracy in object-oriented source code.

Findings

More effective than state-of-the-art methods in reducing coincidental similarities.

Provides more accurate results in detecting plagiarism.

Can generate higher similarity scores with simple abstract method invocation.

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.