• The KIPS Transactions:PartA
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• v.12A no.7 s.97
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• pp.589-596
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• 2005

Source code quality is very Important that software embedded into product is difficult to change. In order to improve source code quality, it should be considered the quality of analysis and design models as well as the quality of source code. In this paper, we suggest 'Practice Pattern' as one of practical techniques to improve embedded software source code quality. Practice pattern is a procedural pattern to guide modeling and coding activities in software development phases. We believe that applying our pattern provides the improvement of optimum performance, modularization, and portability for embedded software source code.

• Journal of Convergence Society for SMB
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• v.6 no.4
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• pp.137-150
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• 2016

Along with the rapid development of IT technology and business services, the effort to provide new services to the customers has been increasing, and also the improvement and enhancement of legacy systems are continuously occurring for rapid service delivery. In this situation, the quality assurance of the source code for the legacy system became a key technical elements that can quickly respond to the service needs. Refactoring is an engineering technique to ensure the quality for the legacy code, and essential for the improvement and extension of the legacy system in order to provide value-added services. This paper proposes some features of refactoring techniques through surveying and analyzing the existing refactoring techniques and tools to enhance source code quality. When service developers want to refactor the source code of the legacy system to enhance code quality, our proposed features may provide with the guidance on what to use any technique and tool in their work. This can improve the source code quality with correct refactoring and without trial and error, and will also enable rapid response to new services.

• Journal of Convergence for Information Technology
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• v.8 no.2
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• pp.91-103
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• 2018

Refactoring is an engineering technique for securing the quality of existing legacy code, improving the internal structure without changing the functionality of the software. Along with the reuse of open source software, reuse of source code through programming language conversion is increasingly required due to technical or market requirements. In this situation, the refactoring technique including language conversion as well as energy efficiency is considered to be an important means for improving the productivity and the quality of embedded software development. This paper proposes a code refactoring technique that converts the grammar and structure of a programming language into those of a different language through comparison and mapping, in addition to the existing energy efficient refactoring technique. The use of the proposed refactoring technique can expect to improve the competitiveness of the product through rapid software development and quality improvement by coping with the environment change of the software development language and enhancing the reuse of the existing code.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.148-153
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• 2015

In our domestic software industries, it is focused on such a high quality development/ testing process, maturity measurement, and so on. But the real industrial fields are still working on a code-centric development. Most of the existing legacy systems did not keep the design and highly increased the code complexity with more patching of the original codes. To solve this problem, we adopt a code visualization technique which is important to reduce the code complexity among modules. To do this, we suggest a tool chaining method based on the existing open source software tools, which extends NIPA's Software Visualization techniques applied to procedural languages. In addition, it should be refactored to fix bad couplings of the quality measurement indicators within the code visualization. As a result, we can apply reverse engineering to the legacy code, that is, from programming via model to architecture, and then make high quality software with this approach.

• 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.

• Journal of Information Technology Services
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• v.17 no.3
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• pp.171-189
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• 2018

To remove software defects and improve performance of software, many developers perform code inspections and use static analysis tools. A code inspection is an activity that is performed manually to detect software defects in the developed source. However, there is no clear criterion which source codes are inspected. A static analysis tool can automatically detect software defects by analyzing the source codes without running the source codes. However, it has disadvantage that analyzes only the codes in the functions without analyzing the relations among source functions. The functions in the source codes are interconnected and formed a social network. Functions that occupy critical locations in a network can be important enough to affect the overall quality. Whereas, a static analysis tool merely suggests which functions were called several times. In this study, the core functions will be elicited by using social network analysis and DEA (Data Envelopment Analysis) for CUBRID open database sources. In addition, we will suggest clear criteria for selecting the target sources for code inspection and will suggest ways to find core functions to minimize defects and improve performance.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.450-454
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• 2015

Short execution time is the major performance factor for computer systems. This performance factor is directly determined by code quality, which is influenced by the compiler's optimizations. However, a compiler has limitations when optimizing source code due to insufficient information. Thus, if programmers can learn the reasons why a compiler fails to apply optimizations, they can rewrite code that is more easily understood by the compiler, and thus improve performance. In this paper, we propose a compiler that provides a programmer with reasons for failed optimization and recognizes programmer's additional information to obtain better optimization. As a result, we obtain performance improvement, i.e., reducing execution time and code size, by taking advantage of additional optimization opportunities.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.5
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• pp.199-206
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• 2023

The current software becomes the huge size of source codes. Therefore it is increasing the importance and necessity of static analysis for high-quality product. With static analysis of the code, it needs to identify the defect and complexity of the code. Through visualizing these problems, we make it guild for developers and stakeholders to understand these problems in the source codes. Our previous visualization research focused only on the process of storing information of the results of static analysis into the Database tables, querying the calculations for quality indicators (CK Metrics, Coupling, Number of function calls, Bad-smell), and then finally visualizing the extracted information. This approach has some limitations in that it takes a lot of time and space to analyze a code using information extracted from it through static analysis. That is since the tables are not normalized, it may occur to spend space and time when the tables(classes, functions, attributes, Etc.) are joined to extract information inside the code. To solve these problems, we propose a regularized design of the database tables, an extraction mechanism for quality metric indicators inside the code, and then a visualization with the extracted quality indicators on the code. Through this mechanism, we expect that the code visualization process will be optimized and that developers will be able to guide the modules that need refactoring. In the future, we will conduct learning of some parts of this process.

• Journal of Ginseng Research
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• v.41 no.3
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• pp.339-346
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• 2017

Background: In this study, we investigated how to convert the Panax ginseng DNA sequence code and chemical fingerprints into a two-dimensional code. In order to improve the compression efficiency, GATC2Bytes and digital merger compression algorithms are proposed. Methods: HPLC chemical fingerprint data of 10 groups of P. ginseng from Northeast China and the internal transcribed spacer 2 (ITS2) sequence code as the DNA sequence code were ready for conversion. In order to convert such data into a two-dimensional code, the following six steps were performed: First, the chemical fingerprint characteristic data sets were obtained through the inflection filtering algorithm. Second, precompression processing of such data sets is undertaken. Third, precompression processing was undertaken with the P. ginseng DNA (ITS2) sequence codes. Fourth, the precompressed chemical fingerprint data and the DNA (ITS2) sequence code were combined in accordance with the set data format. Such combined data can be compressed by Zlib, an open source data compression algorithm. Finally, the compressed data generated a two-dimensional code called a quick response code (QR code). Results: Through the abovementioned converting process, it can be found that the number of bytes needed for storing P. ginseng chemical fingerprints and its DNA (ITS2) sequence code can be greatly reduced. After GTCA2Bytes algorithm processing, the ITS2 compression rate reaches 75% and the chemical fingerprint compression rate exceeds 99.65% via filtration and digital merger compression algorithm processing. Therefore, the overall compression ratio even exceeds 99.36%. The capacity of the formed QR code is around 0.5k, which can easily and successfully be read and identified by any smartphone. Conclusion: P. ginseng chemical fingerprints and its DNA (ITS2) sequence code can form a QR code after data processing, and therefore the QR code can be a perfect carrier of the authenticity and quality of P. ginseng information. This study provides a theoretical basis for the development of a quality traceability system of traditional Chinese medicine based on a two-dimensional code.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.915-934
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• 2020

Software refactoring is a process to restructure an existing software code while keeping its external behavior the same. Currently, various refactoring techniques are being used to develop more readable and less complex codes by improving the non-functional attributes of software. Refactoring can further improve code maintainability by applying various techniques to the source code, which in turn preserves the behavior of code. Refactoring facilitates bug removal and extends the capabilities of the program. In this paper, an exhaustive review is conducted regarding bad smells present in source code, applications of specific refactoring methods to remove that bad smell and its effect on software quality. A total of 68 studies belonging to 32 journals, 31 conferences, and 5 other sources that were published between the years 2001 and 2019 were shortlisted. The studies were analyzed based on of bad smells identified, refactoring techniques used, and their effects on software metrics. We found that "long method", "feature envy", and "data class" bad smells were identified or corrected in the majority of studies. "Feature envy" smell was detected in 36.66% of the total shortlisted studies. Extract class refactoring approach was used in 38.77% of the total studies, followed by the move method and extract method techniques that were used in 34.69% and 30.61% of the total studies, respectively. The effects of refactoring on complexity and coupling metrics of software were also analyzed in the majority of studies, i.e., 29 studies each. Interestingly, the majority of selected studies (41%) used large open source datasets written in Java language instead of proprietary software. At the end, this study provides future guidelines for conducting research in the field of code refactoring.