• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.71-79
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• 2024

ChatGPT, an interactive artificial intelligence (AI) chatbot developed by Open AI in the U.S., gaining popularity with great repercussions around the world. Some academia are concerned that ChatGPT can be used by students for plagiarism, but ChatGPT is also widely used in a positive direction, such as being used to write marketing phrases or website phrases. There is also an opinion that ChatGPT could be a new future for "search," and some analysts say that the focus should be on fostering rather than excessive regulation. This study analyzed consciousness about ChatGPT for college students through a survey of their perception of ChatGPT. And, plagiarism inspection systems were prepared to establish an education support model using ChatGPT and ChatGPT. Based on this, a university education support model using ChatGPT was constructed. The education model using ChatGPT established an education model based on text, digital, and art, and then composed of detailed strategies necessary for the era of the 4th industrial revolution below it. In addition, it was configured to guide students to use ChatGPT within the permitted range by using the ChatGPT detection function provided by the plagiarism inspection system, after the instructor of the class determined the allowable range of content generated by ChatGPT according to the learning goal. By linking and utilizing ChatGPT and the plagiarism inspection system in this way, it is expected to prevent situations in which ChatGPT's excellent ability is abused in education.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.6
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• pp.189-196
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• 2014

Though the plagiarism is illegal and should be avoided, it still occurs frequently. Particularly, the plagiarism of source codes is more frequently committed than others since it is much easier to copy them because of their digital nature. To prevent code plagiarism, there have been reported a variety of studies. However, previous studies for plagiarism detection techniques on source codes do not consider the data structures although a source code consists both of data structures and algorithms. In this paper, a plagiarism detection technique for source codes considering data structures is proposed. Specifically, the data structures of two source codes are represented as sets of trees and compared with each other using Hungarian Method. To show the usefulness of this technique, an experiment has been performed on 126 source codes submitted as homework results in an object-oriented programming course. When both the data structures and the algorithms of the source codes are considered, the precision and the F-measure score are improved 22.6% and 19.3%, respectively, than those of the case where only the algorithms are considered.

• Proceedings of the Korean Society of Computer Information Conference
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• 2010.07a
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• pp.499-502
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• 2010

인터넷의 발달로 인한 수많은 정보의 공유는 지식 정보사회의 발전을 가져왔다. 이러한 정보사회의 발전과 동시에 표절과 같은 새로운 지식 범죄도 급증하고 있다. 표절은 연구의 정직성과 창의성을 떨어뜨리고 학문의 발전을 저해하는 요소이다. 이러한 표절을 근절하기 위해서 그동안 많은 방법들과 시스템들이 제시되었다. 이중 자연어로 구성된 구조가 없는 일반 문서의 표절을 검사하는 방법은 지문법을 이용하였다. 지문법과 같이 통계적인 방법을 이용한 유사도 검사 방법은 문서 대 문서 전체를 비교하기 때문에 부분적 유사성, 즉 문장이나 문단 단위의 비교를 할 수 없는 단점이 있다. 본 논문에서 제시하는 시스템은 자연어로 이루어진 일반문서 중 특별한 문서의 구조 정보를 가질 수 있는 일반 텍스트 문서를 대상으로 유사도를 측정하였다. 즉 텍스트 문서 구조를 AST 형태의 자료구조로 표시하고 이를 이용하여 사용자가 원하는 부분 또는 전체 유사도 측정 방법을 제시한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.147-150
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• 2006

본 논문에서는 각종 언어로 구현된 프로그램의 소스 코드를 표절 하였을 경우 이를 효과적으로 탐지하는 방법과 이론을 제시하고자 한다. 기존에 사용되고 있는 프로그램 표절(plagiarism) 검사 소프트웨어의 장단점을 분석하고, 특히 단점을 극복하기 위한 방법으로 Pattern Matching을 이용한 표절 검출방법을 소개한다. 그리고 기존의 Pattern Matching을 이용한 방법에서 나타나는 문제점을 극복하여 좀 더 발전된 방식의 자동 표절 검출 시스템을 소개하고자 한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.511-514
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• 2009

Recently web is used for more things than ever before in education. Previous web-based programming education systems help students to check compile errors and runtime errors after submitting programming assignments anytime and anywhere. However, these previous systems cannot quickly provide the detailed assessment results on the generated answer, the coding style, and the plagiarism detection. In this paper, we propose a web-based programming education system to provide the quick results of the detailed assessment as soon as to submit programming assignments. In this system, the plagiarism detection method compares a current file with only the already uploaded files so it can provide quick feedback. The proposed web-based programming education system is applied to a real C programming language class with approximately 40 students. The proposed system tends to improve the students' participation by quick feedback.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.727-729
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• 2004

최근 논문의 표절 및 저작권과 관련하여 여러 가지 사건들이 일어나 많은 관심과 우려를 불러일으키고 있다. 특히 인터넷 통신의 발달 및 워드프로세서의 기능 향상으로 인해 일선 교육현장에서의 표절에 간한 문제는 더욱 커지고 있다. 하지만 문서의 표절 여부를 가려내는 작업은 쉬운 일이 아니다. 과제로 제출되는 일반 문서의 경우 본문의 내용이나 문서의 개수를 고려해 볼 때 사람이 직접 표절 여부를 검사하는 것은 매우 힘든 작업이다. 그리고 어간, 어미의 변형이 쉽게 일어날 수 있는 한글의 경우에는 영어에서처럼 어절 단위로 두 문서를 비교하여 표절여부를 판정하는 기존의 방법은 적합하지가 않다 본 논문에서는 한글로 작성된 텍스트 문서의 표절 여부를 효과적으로 검출해 내기 위한 새로운 방법들을 제시하고 있다. 그리고 실제로 수집된 다양한 문서 데이터 집합들에 대해 각각의 방법들을 테스트해 보고 실제 데이터에서 가장 효율적인 방범이 어떤 깃인지 제시한다

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.3
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• pp.352-367
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• 2003

The syntactic and semantic characteristics of a computer program can be represented by the keywords sequence extracted from the source code. Therefore the similarity and the difference between two programs can be clearly figured out by comparing the keyword sequences obtained from the given programs. Various methods for measuring the similarity of two different sequences have been intensively studied already in bioinformatics on biological genetic sequence manipulation. In this paper, we propose a new method for measuring the similarity of two different programs and detecting the partial plagiarism by exploiting the sequence alignment techniques. In order to evaluate the performance of the proposed method, we experimented with the actual Program codes submitted by 70 students attending a Data Structure course )tow 2001. The experimental results show that the proposed method is more effective and powerful than the fingerprint method which is the most commonly used for the Plagiarism detection.

• Journal of Software Assessment and Valuation
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• v.14 no.2
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• pp.35-44
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• 2018

Tools for detecting cross-language clones usually compare abstract-syntax-tree representations of source code, which lacks scalability. In order to compare large source code to a practical level, we need a similarity checking technique that works on a token level basis. In this paper, we define common tokens that represent all tokens commonly used in programming languages of different paradigms. Each source code of different language is then transformed into the list of common tokens that are compared. Experimental results using exEyes show that our proposed method using common tokens is effective in detecting cross-language clones.

• Journal of KIISE:Software and Applications
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• v.32 no.4
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• pp.290-299
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• 2005

Stealing the source code of a program is a serious problem not only in a moral sense but also in a legal sense. However, it is not clear whether the code of a program is copied from another or not. There was a program similarity checker detecting code-copy by comparing the syntax trees of programs. However this method has a limitation that it cannot detect the code-copy attacks when the attacker modifies the syntax of the program on purpose. We propose a program similarity check by program control graph, which reveals not only syntax information but also control dependancy. Our method can detect the code-copy attacks that do not change control dependancy Moreover, we define what code-copy means and establish the connection between code-copy and similarity of program control graph: we prove that two programs are related by copy congruence if and only if the program control graphs of these programs are equivalent. We implemented our method on a functional programming language, nML. The experimental results show us that the suggested method can detect code similarity that is not detected by the existing method.

• The Journal of Korean Association of Computer Education
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• v.13 no.6
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• pp.79-89
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• 2010

In this paper, we proposed a method to find out similar sentences from documents to detect plagiarized documents. The proposed model adapts LSA and N-gram techniques to detect every type of Korean plagiarized sentence type. To evaluate the performance of the model, we constructed experimental data using students' essays on the same theme. Students made their essay by intentionally plagiarizing some reference documents. The experimental results showed that our proposed model outperforms the conventional N-gram model, Vector model, LSA model in precision, recall, and F measures.