• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.39-47
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• 2021

Lempel-Ziv coding is one of the most famous source coding schemes. The output of this source coding is usually a non-uniform code, which requires additional source coding, such as arithmetic coding, to reduce a redundancy. However, this additional source code increases complexity and decoding latency. Thus, this paper proposes the optimal maximum a-posteriori (MAP) receiver for non-uniform source non-orthogonal multiple access (NOMA) with symmetric superposition coding (SSC). First, we derive an analytical expression of the bit-error rate (BER) for non-uniform source NOMA with SSC. Then, Monte Carlo simulations demonstrate that the BER of the optimal MAP receiver for the non-uniform source improves slightly, compared to that of the conventional receiver for the uniform source. Moreover, we also show that the BER of an approximate analytical expression is in a good agreement with the BER of Monte Carlo simulation. As a result, the proposed optimal MAP receiver for non-uniform source could be a promising scheme for NOMA with SSC, to reduce complexity and decoding latency due to additional source coding.

• Journal of the Korea Society of Computer and Information
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• v.21 no.8
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• pp.65-75
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• 2016

In this paper, we present a novel approach to help MSR researchers obtain necessary data with a tool, termed General Purpose Extractor for Source code (GPES). GPES has a single function extracts high-quality data, e.g., the version history, abstract syntax tree (AST), changed code diff, and software quality metrics. Moreover, features such as an AST of other languages or new software metrics can be extended easily given that GPES has a flexible data model and a component-based design. We conducted several case studies to evaluate the usefulness and effectiveness of our tool. Case studies show that researchers can reduce the overall cost of data analysis by transforming the data into the required formats.

• KIISE Transactions on Computing Practices
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• v.23 no.8
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• pp.487-491
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• 2017

Open source software allows the users to freely use, copy, distribute and modify source code without any particular limitations, and this offers the advantages of low entry cost, fast and flexible development, compatibility, reliability and safety. The emergence of many useful open source projects has the advantage of achieving high levels of output with lower costs and time commitment for software development. However, this also increases the risks caused by the security vulnerabilities of the used open source software. There is still no separate process to verify security in using open source software. In this paper, we analyze the security weakness in open source and propose a secure coding scheme in adopting open source, which is known to be highly reliable from a security point of view.

• The Transactions of the Korea Information Processing Society
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• v.5 no.8
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• pp.2041-2049
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• 1998

This paper suggests a technique for program segmentation and maintenance using PSDG(Post-State Dependency Graph) that improves the quality of a software by identifying and detecting defects in already fixed source code. A program segmentation is performed by utilizing source code analysis which combines the measures of static, dynamic and semantic slicing when we need understandability of defect in programs for corrective maintanence. It provides users with a segmental principle to split a program by tracing state dependency of a source code with the graph, and clustering and highlighting, Through a modeling of the PSDG, elimination of ineffective program deadcode and generalization of related program segments arc possible, Additionally, it can be correlated with other design modeb as STD(State Transition Diagram), also be used as design documents.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.129-137
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• 2020

Recently, software size and program code complexity have increased due to application to various fields of software. Accordingly, the existence of program bugs inevitably occurs, and the cost of software maintenance is increasing. In open source projects, developers spend a lot of debugging time when solving a bug report assigned. To solve this problem, in this paper, we apply SeqGAN algorithm to software bug repair. In detail, the SeqGAN model is trained based on the source code. Open similar source codes during the learning process are also used. To evaluate the suitability for the generated candidate patch, a fitness function is applied, and if all test cases are passed, software bug correction is considered successful. To evaluate the efficiency of the proposed model, it was compared with the baseline, and the proposed model showed better repair.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1684-1685
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• 2007

Development of software for microprocessors is one of the areas where UML can be used. There are many UML tools which is capable of generating source code for microprocessors. In this paper, a part of CANopen protocol is implemented using UML and the source code generated by a UML tool is tested.

• Journal of Convergence for Information Technology
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• v.7 no.4
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• pp.69-74
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• 2017

ICT(Information Communication Technology) is a key word in our society on today. Various support programs by the government have given many quantitative and qualitative changes to the software industries. Software is instructions(Computer Program) and data structure. Software can be divided into Application program and System program. Application programs have been developed to perform special functions or provide entertainment functions. Because of this rapid growth of software industries, one of the problems is issue on copyright of program. In this paper, we described an analysis method for program similarity based on source code in program.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.237-245
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• 2022

The prominence of IoTs (Internet of Things) and exponential advancement of computer networks has resulted in massive essential applications. Recognizing various cyber-attacks or anomalies in networks and establishing effective intrusion recognition systems are becoming increasingly vital to current security. MLTs (Machine Learning Techniques) can be developed for such data-driven intelligent recognition systems. Researchers have employed a TFDNNs (Tensor Flow Deep Neural Networks) and DCNNs (Deep Convolution Neural Networks) to recognize pirated software and malwares efficiently. However, tuning the amount of neurons in multiple layers with activation functions leads to learning error rates, degrading classifier's reliability. HTFDNNs ( Hybrid tensor flow DNNs) and MRNs (Modified Residual Networks) or Resnet CNNs were presented to recognize software piracy and malwares. This study proposes HTFDNNs to identify stolen software starting with plagiarized source codes. This work uses Tokens and weights for filtering noises while focusing on token's for identifying source code thefts. DLTs (Deep learning techniques) are then used to detect plagiarized sources. Data from Google Code Jam is used for finding software piracy. MRNs visualize colour images for identifying harms in networks using IoTs. Malware samples of Maling dataset is used for tests in this work.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1234-1249
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• 2017

One of the difficulties developers encounter in maintaining tasks of a large-scale software system is the updating of suitable libraries on time. Developers tend to miss or make mistakes when searching for and choosing libraries during the development process, or there may not be a stable library for the developers to use. We present a novel approach for helping developers modify software easily and on time and avoid software failures. Using a tool previously built by us called GPES, we collected information of projects, such as abstract syntax trees, tokens, software metrics, relations, and evolutions, for our experiments. We analyzed the contexts of source codes in existing projects to predict changes automatically and to recommend suitable libraries for the projects. The collected data show that researchers can reduce the overall cost of data analysis by transforming the extracted data into the required input formats with a simple query-based implementation. Also, we manually evaluated how the extracted contexts are similar to the description and we found that a sufficient number of the words in the contexts is similar and it might help developers grasp the domain of the source codes easily.

• Journal of IKEEE
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• v.19 no.2
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• pp.186-192
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• 2015

This paper proposes an automatic generation technology of test case based on API in source code for software's quality improvement. The proposed technology is comprised of four processes which are analyzing source code by using the Doxygen open source tool, defining API specification by using analyzed results, creating test design, generating a test case by adapting Pairwise test technology. Analyzing source code by using the Doxygen open source tool is the phase in which API information in source code such as the API name, input parameter and return parameter are extracted. Defined API specification by using analyzed results is the phase where API informations, which is needed to generate test case, are defined as a form of database by SQLite database on the basis of extracted API information. Creating test design is the phase in which the scenario is designed in order to be composed as database by defining threshold of input and return parameters and setting limitations based on the defined API. Generating a test case by adapting Pairwise test technique is the phase where real test cases are created and changed into database by adapting Pairwise technique on the base of test design information. To evaluate the efficiency of proposed technology, the research was conducted by begin compared to specification based test case creation. The result shows wider test coverage which means the more cases were created in the similar duration of time. The reduction of manpower and time for developing products is expected by changing the process of quality improving in software developing from man-powered handwork system into automatic test case generation based on API of source code.