Plagiarism detection

About: Plagiarism detection is a research topic. Over the lifetime, 1790 publications have been published within this topic receiving 24740 citations.

System, Method, and Computer-Readable Medium for Plagiarism Detection

Abstract: A system, method, and computer-readable medium for detecting plagiarism in a set of constructed responses by accessing and pre-processing the set of constructed responses to facilitate the pairing and comparing of the constructed responses. The similarity value generated from the comparison of a pair of constructed responses serves as an indicator of possible plagiarism.

An Experience on Ada Programming Using On-Line Judging

Abstract: Ada has proved to be one of the best languages to learn computer programming. Nevertheless, learning to program is difficult and when it is combined with lack of motivation by the students, dropout rates can reach up to 70%. In order to face up to this problem, we have developed a first-year course for computing majors on programming based on two key ideas: supplementing the final exam with a series of activities in a continuous evaluation context; and making those activities more appealing to the students. In particular, some of the activities are designed as on-line Ada programming competitions; they are carried out by using a web-based automatic evaluation system, the on-line judge. Human instructors remain essential to assess the quality of the code. To ensure the authorship of the programs, a source-code plagiarism detection environment is used. Experimental results show the effectiveness of the proposed approach. The dropout rate decreased from 61% in the autumn semester 2007 to 48% in the autumn semester 2008.

Advice for Plagiarism Whistleblowers

Abstract: Scholarly open-access publishing has made it easier for researchers to discover and report academic misconduct such as plagiarism. However, as the website Retraction Watch shows, plagiarism is by no means limited to open-access journals. Moreover, various web-based services provide plagiarism detection software, facilitating one’s ability to detect pirated content. Upon discovering plagiarism, some are compelled to report it, but being a plagiarism whistleblower is inherently stressful and can leave one vulnerable to criticism and retaliation by colleagues and others (Anderson, 1993; Cabral-Cardoso, 2004). Reporting plagiarism can also draw the threat of legal action. This article draws upon our experiences as plagiarism whistleblowers with several goals in mind: to help would-be whistleblowers be better prepared for making well-founded allegations, to give whistleblowers some idea of what they can expect when reporting plagiarism, and to give suggestions for reducing whistleblowers’ vulnerability to thre...

Syntax-based Improvements to Plagiarism Detectors and their Evaluations

Abstract: Software plagiarism cheats students out of their own education and leads to unfair grading, making software plagiarism detection an important problem. However, many popular plagiarism detection tools are inaccurate, language-specific, or closed source, limiting their applicability. In this work, we seek to address these problems via a novel approach. We adapt the optimal Smith-Waterman sequence alignment algorithm to precisely measure the similarity between programs, greatly improving detection accuracy relative to competitors. Our approach is applicable to any language describable by an ANTLR grammar, which includes most programming languages. We also provide a new type of evaluation based on random program generation and obfuscation. Finally, we make our approach freely available, allowing for customizations and transparent reasoning about detection behavior.

Automatic detection of local reuse

Abstract: Local reuse detection is a prerequisite for a multitude of tasks ranging from document management and information retrieval to web search or plagiarism detection. Its results can be used to support authors in creating new learning resources or learners in finding existing ones by providing accurate suggestions for related documents. While the detection of local text reuse, i.e. reuse of parts of documents, is covered by various approaches, reuse detection for object-based documents has been hardly considered yet. In this paper we propose a new fingerprinting technique for local reuse detection for both text-based and object-based documents which is based on the contiguity of documents. This additional information, which is generally disregarded by existing approaches, allows the creation of shorter and more flexible fingerprints. Evaluations performed on different corpora have shown that it performs better than existing approaches while maintaining a significantly lower storage consumption.