• The KIPS Transactions:PartD
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• v.13D no.5 s.108
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• pp.717-724
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• 2006

The cost estimation of software is getting more important as the portion of software is increasing in acquiring weapon systems. However, the cost estimation of embedded software in a weapon system follows the cost estimation method for general purpose softwares and uses the PRICE S model as a tool. However, any validation result of the estimated cost through an evaluated software size is not well known. Hence, we propose an approach to estimate the cost through evaluating the embedded software site in weapon systems. In order to achieve our research goal, we evaluate the software size of using the line of codes and function points which are produced by the PRICE S model. Finally, we compare the estimated cost data the actual cost data provided by the production company. As a result, we propose an approach to estimate the size and the cost of embedded software in weapon systems which are not easy to estimate objectively. We also expect that the Proposed approach is used for the cost validation and negotiation in the acquisition of weapon systems in the future.

• Proceedings of the PSK Conference
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• 2004.10a
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• pp.140-140
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• 2004

• Journal of Electrical Engineering and Technology
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• v.2 no.3
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• pp.386-390
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• 2007

At recent times, an essential issue in the replacement of the old analogue I&C to computer-based digital systems in nuclear power plants becomes the quantitative software reliability assessment. Software reliability models have been successfully applied to many industrial applications, but have the unfortunate drawback of requiring data from which one can formulate a model. Software that is developed for safety critical applications is frequently unable to produce such data for at least two reasons. First, the software is frequently one-of-a-kind, and second, it rarely fails. Safety critical software is normally expected to pass every unit test producing precious little failure data. The basic premise of the rare events approach is that well-tested software does not fail under normal routine and input signals, which means that failures must be triggered by unusual input data and computer states. The failure data found under the reasonable testing cases and testing time for these conditions should be considered for the quantitative reliability assessment. We presented the quantitative reliability assessment methodology of safety critical software for rare failure cases in this paper.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.6
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• pp.247-252
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• 2015

As software has gotten bigger in magnitude and the complexity of software has been increased, the maintenance has gained in-creasing attention for its significant impact on the cost. Identifiers have an impact on more than 90 percent of the readability which accounts for a majority portion of the maintenance activities. For this reason, the existing works focus on domain-specific features based on identifiers. However, their approaches have a limitation when either a class name does not reflect the intention of its context or a class naming is incorrect. Therefore, this paper suggests a series of class name validation process by extracting properties of classes, building learning model by applying a decision tree technique of machine learning, and generating a validation report containing the list of recommendable postfixes of classes to be validated. To evaluate this, four open source projects are selected and indicators such as precision, recall, and ROC curve present the value of this work when it comes to five specific postfixes including functional information on class names.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.1-6
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• 1998

The evaluation of reliability is very important in the development process of software. There may be lack of trustfulness on the results that come from the analysis and evaluation of reliability of softwares which do not divide the test phases. At this point, this article studies how to evaluate the reliability dividing the test phases in order to settle the these problems. In doing so, I apply the fault data to be found in Unit Test, Integration Test, Validation Test and System Test to SRGM(Software Reliability Growth Model), Exponential SRGM, Delayed S-shaped SRGM and Inflection S-shaped SRGM. The result is that Inflection S-shaped is best suitable with Unit Test Delayed S-shaped is best suitable with Integration and Validation Test, and Exponential SRGM is best suitable with System test. In this respect, I can show that the results of this study on parameter estimation, difference square summation, number of fault remained is superior to the established methods.

• Journal of the Korean Society of Systems Engineering
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• v.14 no.2
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• pp.83-88
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• 2018

Software has become an integral part of almost any system, triggered by the ever-growing demand for automation and artificial intelligent throughout engineering domains. The complexities of software-centric systems are also increasing, which make software test efforts become essential in software development projects. In this study, we applied systems engineering methodology in generating software test cases. We found out the similarities between requirements analysis and traceability concept of systems engineering and test specification contents of software test. In terms of acceptance test, software test cases could be considered as validation requirements. We also suggested a method to determine test order using a SysML modeling tool.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.9
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• pp.275-284
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• 2016

The software used in the nuclear safety field has been ensured through the development, validation, safety analysis, and quality assurance activities throughout the entire process life cycle from the planning phase to the installation phase. However, this evaluation through the development and validation process needs a lot of time and money, and there are limitations to ensure that the quality is improved enough. Therefore, the effort to calculate the reliability of the software continues for a quantitative evaluation instead of a qualitative evaluation. In this paper, we propose a reliability evaluation method for the software to be used for a specific operation of the digital controller in a nuclear power plant. After injecting weighted faults in the internal space of a developed controller and calculating the ability to detect the injected faults using diagnostic software, we can evaluate the software reliability of a digital controller in a nuclear power plant.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.3
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• pp.1-19
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• 2002

Recently, increasing attention has been paid to building a successful software process in Information System(IS) implementation. This study establishes software process model as a key predictor of organizational performance. We propose a theoretical framework for capability maturity model derived from the Software Engineering Institute(SEI). This paper identify the process-related variables, financial performance and non-financial performance from the relevant literature and clarify the concept of software process by distinguishing between its component and determinants. We then examine the impact of software process on organizational performance. Hypotheses on software process were tested for 36 enterprises including 118 organizational units. Results indicate that software process capability may serve as a key predictor of organizational performance. Software process maturity found to be positively influenced on the financial and non-financial performance, while investment of information technology as a mediating variable not significantly affected to the performance.

• Journal of the Korean Medical Association
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• v.61 no.12
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• pp.765-775
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• 2018

With growing interest in novel digital healthcare devices, such as artificial intelligence (AI) software for medical diagnosis and prediction, and their potential impacts on healthcare, discussions have taken place regarding the regulatory approval, coverage, and clinical implementation of these devices. Despite their potential, 'digital exceptionalism' (i.e., skipping the rigorous clinical validation of such digital tools) is creating significant concerns for patients and healthcare stakeholders. This white paper presents the positions of the Korean Society of Radiology, a leader in medical imaging and digital medicine, on the clinical validation, regulatory approval, coverage decisions, and clinical implementation of novel digital healthcare devices, especially AI software for medical diagnosis and prediction, and explains the scientific principles underlying those positions. Mere regulatory approval by the Food and Drug Administration of Korea, the United States, or other countries should be distinguished from coverage decisions and widespread clinical implementation, as regulatory approval only indicates that a digital tool is allowed for use in patients, not that the device is beneficial or recommended for patient care. Coverage or widespread clinical adoption of AI software tools should require a thorough clinical validation of safety, high accuracy proven by robust external validation, documented benefits for patient outcomes, and cost-effectiveness. The Korean Society of Radiology puts patients first when considering novel digital healthcare tools, and as an impartial professional organization that follows scientific principles and evidence, strives to provide correct information to the public, make reasonable policy suggestions, and build collaborative partnerships with industry and government for the good of our patients.

• Journal of Distribution Science
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• v.13 no.1
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• pp.57-70
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• 2015

Purpose - Open source software has high utilization in most of the server market. The utilization of open source software is a global trend. Particularly, Internet infrastructure and platform software open source software development has increased rapidly. Since 2003, the Korean government has published open source software promotion policies and a supply promotion policy. The dynamism of the open source software market, the lack of relevant expertise, and the market transformation due to reasons such as changes in the relevant technology occur slowly in relation to adoption. Therefore, this study proposes an assessment model of services provided in an open source software service company. In this study, the service level of open source software companies is classified into an enterprise-level assessment area, the service level assessment area, and service area. The assessment model is developed from an on-site driven evaluation index and proposed evaluation framework; the evaluation procedures and evaluation methods are used to achieve the research objective, involving an impartial evaluation model implemented after pilot testing and validation. Research Design, data, and methodology - This study adopted an iteration development model to accommodate various requirements, and presented and validated the assessment model to address the situation of the open source software service company. Phase 1 - Theoretical background and literature review Phase 2 - Research on an evaluation index based on the open source software service company Phase 3 - Index improvement through expert validation Phase 4 - Finalizing an evaluation model reflecting additional requirements Based on the open source software adoption case study and latest technology trends, we developed an open source software service concept definition and classification of public service activities for open source software service companies. We also presented open source software service company service level measures by developing a service level factor analysis assessment. The Behavior-Structure-Evolution Evaluation Model (BSEM) proposed in this study consisted of a rating methodology for calculating the level that can be granted through the assessment and evaluation of an enterprise-level data model. An open source software service company's service comprises the service area and service domain, while the technology acceptance model comprises the service area, technical domain, technical sub-domain, and open source software name. Finally, the evaluation index comprises the evaluation group, category, and items. Results - Utilization of an open source software service level evaluation model For the development of an open source software service level evaluation model, common service providers need to standardize the quality of the service, so that surveys and expert workshops performed in open source software service companies can establish the evaluation criteria according to their qualitative differences. Conclusion - Based on this evaluation model's systematic evaluation process and monitoring, an open source software service adoption company can acquire reliable information for open source software adoption. Inducing the growth of open source software service companies will facilitate the development of the open source software industry.