AntiPlag: Plagiarism Detection on Electronic Submissions of Text Based Assignments

Plagiarism is one of the growing issues in academia and is always a concern in Universities and other academic institutions. The situation is becoming even worse with the availability of ample resources on the web. This paper focuses on creating an effective and fast tool for plagiarism detection for text based electronic assignments. Our plagiarism detection tool named AntiPlag is developed using the tri-gram sequence matching technique. Three sets of text based assignments were tested by AntiPlag and the results were compared against an existing commercial plagiarism detection tool. AntiPlag showed better results in terms of false positives compared to the commercial tool due to the pre-processing steps performed in AntiPlag. In addition, to improve the detection latency, AntiPlag applies a data clustering technique making it four times faster than the commercial tool considered. AntiPlag could be used to isolate plagiarized text based assignments from non-plagiarised assignments easily. Therefore, we present AntiPlag, a fast and effective tool for plagiarism detection on text based electronic assignments

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

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.Comment: The 8th International Conference on Software Engineering and Service Scienc

Dynamic Thresholding Mechanisms for IR-Based Filtering in Efficient Source Code Plagiarism Detection

To solve time inefficiency issue, only potential pairs are compared in string-matching-based source code plagiarism detection; wherein potentiality is defined through a fast-yet-order-insensitive similarity measurement (adapted from Information Retrieval) and only pairs which similarity degrees are higher or equal to a particular threshold is selected. Defining such threshold is not a trivial task considering the threshold should lead to high efficiency improvement and low effectiveness reduction (if it is unavoidable). This paper proposes two thresholding mechanisms---namely range-based and pair-count-based mechanism---that dynamically tune the threshold based on the distribution of resulted similarity degrees. According to our evaluation, both mechanisms are more practical to be used than manual threshold assignment since they are more proportional to efficiency improvement and effectiveness reduction.Comment: The 2018 International Conference on Advanced Computer Science and Information Systems (ICACSIS

The Effectiveness of Low-Level Structure-based Approach Toward Source Code Plagiarism Level Taxonomy

Low-level approach is a novel way to detect source code plagiarism. Such approach is proven to be effective when compared to baseline approach (i.e., an approach which relies on source code token subsequence matching) in controlled environment. We evaluate the effectiveness of state of the art in low-level approach based on Faidhi \& Robinson's plagiarism level taxonomy; real plagiarism cases are employed as dataset in this work. Our evaluation shows that state of the art in low-level approach is effective to handle most plagiarism attacks. Further, it also outperforms its predecessor and baseline approach in most plagiarism levels.Comment: The 6th International Conference on Information and Communication Technolog

Performance Evaluation of Plagiarism Detection Method Based on the Intermediate Language

This paper presents detection method for source code plagiarism that is based on the intermediate language, and shows its usage in e-learning. Method is tested on the appropriate number of test cases that represent the most frequent code modification techniques. Results and its performance are compared to the existing source code plagiarism detection methods implemented in some of the most known plagiarism detection systems and applications

Automated assessment in a programming course for mathematicians

The paper reports on a programming course for undergraduate Mathematics students in their 2nd year, with some parts compulsory for single-subject students. Assessment takes the form of several programming projects. Formative feedback as well as summative assessment is aided by automated unit tests, which allow for rapid and consistent marking, while focussing marker’s time on students who require the most help