Gyun Woo

A source code linearization technique for detecting plagiarized programs

It is very important to detect plagiarized programs in the field of computer science education. Therefore, many tools and algorithms have been developed for this purpose. Generally, these tools are operated in two phases. In phase 1, a program plagiarism detecting tool generates an intermediate representation from a given program set. The intermediate representation should reflect the structural characterization of the program. Most tools use the parse tree or token sequence by intermediate representation. In phase 2, the program looks for plagiarized material and evaluates the similarity of two programs. It is helpful to announce the plagiarized metarials between two programs to the instructor. In this paper, we present the static tracing method in order to improve program plagiarism detection accuracy. The static tracing method statically executes a program at the syntax-level and then extracts predefined keywords according to the order of the executed functions. The result of experiment proves this method can detect plagiarism more effectively than the previously released plagiarism detecting method.

Detecting and tracing plagiarized documents by reconstruction plagiarism-evolution tree

Due to smart word processors and powerful Web-searching engines, lots of plagiarism prevail, especially in digital texts. So it is very crucial to develop efficient and effective anti-plagiarism tools to prevent or identify document plagiarism. Till now, a few plagiarism detecting systems have been announced. All previous plagiarism detection studies focus on how to measure the similarity of documents. In this paper, we propose a new approach to reconstruct the evolution process of suspected texts in order to detect plagiarized documents. For this, we propose two major metrics: spatial plagiarism similarity and temporal plagiarism similarity. And by combining these two similarity measure, we give conclusively the evolutionary plagiarism probability model by adopting the Weibull distribution, which is one of extreme distribution used to compute the statistical significance of genomic sequence matching. The main difference of our model to the previous studies is that our model can estimate the plagiarism and its direction as a temporal event. An experiment with a group Internet-posted news clearly coincided to the real plagiarism among those news.

Yet another paper ranking algorithm advocating recent publications

In this paper, we propose a new paper ranking algorithm that gives a high rank to papers which is credited by other authoritative papers or published in premier conferences or journals. Also, the proposed algorithm solves a problem that recent papers are rated poorly due to few citations.

Software plagiarism detection via the static API call frequency birthmark

In this paper, we propose a system for detecting software plagiarism using a birthmark. The birthmark is representative features of a program, which can be used to identify the program. We use a set of frequency of APIs used in a program as its birthmark. The proposed system consists of three components. First, it extracts the frequency of APIs employed in a program. Next, it generates the program birthmark using a set of frequency of APIs and weights to APIs to extract unique features of the program. Finally, it decides the plagiarism based on the cosine similarity between the birthmarks. Through extensive experiments, it was found that the proposed system can provide 97.2% of precision and 95.7% of recall in plagiarism detection.

Source Code Similarity Detection Using Adaptive Local Alignment of Keywords

Program similarity checking is an important application of programming education fields. Local alignment is one of the typical algorithms for comparing two strings. However local alignment based comparison does not reflect the weights of program keywords. This paper introduces an adaptive local alignment which reflects the frequencies of keywords to the similarity matrix. We experimented this method using a set of programs submitted to more than 10 real programming contests. The experimental result shows that the adaptive local alignment is more robust than greedy-string-tiling adopted in JPlag.

Revising cohesion measures by considering the impact of write interactions between class members

Cohesion refers to the degree of the relatedness of the members in a class and several cohesion measures have been proposed to quantify the cohesiveness of classes in an object-oriented program. However, the existing cohesion measures do not differentiate write interactions from read interactions between class members, thus, do not properly reflect the cohesiveness of the class. This paper presents the revised versions of the existing five cohesion measures by considering the impact of write interactions between class members. In addition, we prove that the revised measures can be reduced into the original ones. To demonstrate the importance of write interactions, we have developed tools for automatic computation of the original and the revised cohesion measures and performed a case study where we found that write interactions are so commonly used in classes that they have much influence on cohesion measurement and the revised measures have stronger relations with change-proneness of classes than the original ones.

Understanding the evolution process of program source for investigating software authorship and plagiarism

This paper addresses the evolution process of program source codes to establish the framework for software authorship identification. Since program code cheating is getting serious in academic institutions, we will be able to apply the software authorship identification tool as a detection tool for code plagiarism. The main contribution of our work is twofold. First, we have devised new asymmetric distance measure to compute the distance of authorship between two different programs. Second, we have proposed an algorithm to construct the evolution tree(hylogenetic tree) for a set of similar program clones. For the experiment we have gathered two set of codes: a set of assignment programs and another program set which have been submitted to the ICPC, an international programming contests. Our experiment showed that our distance measure for program sources has successfully identified the code authorship and has also reliably detected plagiarized programs. This experiment has showed a strong possibility that the proposed construction algorithm for phylogenetic forest can be used to trace the evolution(improving) process of software. This paper shows the confidence of the authorship identification and plagiarism detection can be interchangeably applied for both these purposes in student assignment program domain.

Analysis and Visualization for Comment Messages of Internet Posts

There are many internet users who collect the public opinions and express their opinions for internet news or blog articles through the replying comment on online community. But, it is hard to search and explore useful messages on web blogs since most of web blog systems show articles and their comments to the form of sequential list. Also, spam and malicious comments have become social problems as the internet users increase. In this paper, we propose a clustering and visualizing system for responding comments on large-scale weblogs, namely `Daum AGORA,` using similarity analysis. Our system shows the comment clustering result as a simple screen view. Our system also detects spam comments using Needleman-Wunsch algorithm that is a well-known algorithm in bioinformatics.

Design and Implementation of Retargetable Software Debugger Based on GDB

Many processors for embedded system have been developed and is widely being used in many industrial area. If we develop a new embedded processor, we need a simulator, compiler, and debugger for developing an operating system and basic program running on the embedded processor. The debugger is used for finding the error in a program. theses software are very important in embedded system. In this paper, we design and implement a retargetable software debugger for a new 32-bit microprocessor. Our software debugger is based on GNU debugger (GDB) which is a widely used open-source debugger. We explain how to develop a retagetable software debugger for a new embedded processor rapidly. In order to develop a debugger rapidly, we extended only processor-dependent modules for register, memory and instruction set. And, we reused the processor-independent modules in the debugger. In the experiment, we tried to compare our software debugger with ARM AXD debugger to verify the debugger operation. The ARM AXD Debugger is well-known debugger for ARM processor.

Automatic Generation Algorithm of FAST Protocol Templates for Efficient Transmission of Financial Data

The protocol FAST (FIX adapted for streaming) is superior than FIX in that it performs data compression according to the protocol template prescribed. Since the FAST protocol template captures the sequence characteristic of the transmitted data, it is written manually by human experts. This paper describes an algorithm for generating FAST protocol templates automatically by analyzing the patterns of message sequence. The experimental result shows that the proposed algorithm is slightly more efficient than the human expert in respects of the compression ratio.