• 한국컴퓨터정보학회논문지
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• 제25권11호
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• pp.147-155
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• 2020

체계지원 소프트웨어는 함정 전투관리체계를 구성하는 소프트웨어 중의 하나로 모든 함정의 전투관리체계에 탑재되지만 기능 변경이 거의 일어나지 않는 특성을 가진다. 하지만, 이러한 특성에도 실제로는 신규함정 적용 시 장비 변경 등으로 인한 소프트웨어 수정이 불가피하게 이루어진다. 이러한 소프트웨어의 수정은 소프트웨어 신뢰성 시험 등의 작업을 초래하며, 개발 비용 증가의 핵심요인으로 작용한다. 본 논문에서는 기존 체계지원 소프트웨어의 구조를 분석하여 이를 보완할 수 있는 체계지원 표준화 아키텍처를 설계하였다. 휘처 모델(Feature Model)을 통해 체계지원 소프트웨어의 공통요소와 가변요소를 도출하고, 화이트 박스 재사용(White-Box Reuse)을 적용하여 소프트웨어 설계를 개선하였다. 또한, 기존 체계지원 소프트웨어와 개발 요소 및 신뢰성 시험 수행 시간을 비교하여 새로운 아키텍처의 효과성을 검증한 결과를 제시하였다.

• 한국컴퓨터정보학회논문지
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• 제23권4호
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• pp.175-182
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• 2018

In this paper, we propose a software education ecosystem model for activating software education donation. First, in order to investigate current software education donation status, we will conduct a survey on software education donors and analyze the results. 39.6% of the software education donors responded that they were introduced to software education donation activities through their affiliated companies, institutions, organizations. Therefore, it can be seen that the promotion of software education donation activities is the most effective by promoting through software companies, organizations, and organizations and using human networks. The subjects of software education donation activities were the highest at middle school students (73.9%), and the contents of software education donations were the highest at programming practice (63.3%). Donors' satisfaction with software education donation activities was 57.9%. The social support for SW education donors was in the order of software education contents support, activity cost support, equipment and network support, and place sponsorship. 87.4% of donors were willing to continue to donate to software education. The reason why they did not want to continue donating software education was 'lack of personal time' (65.4%). Therefore, it is necessary to develop appropriate social support and incentive system to overcome shortage of personal time in order to activate software education contribution. In order to promote sustainable software education donations, it is essential to establish a virtuous circle of software education donation ecosystem based on cooperation and solidarity with various organizations such as government, corporations, institutions, universities and civil society organizations.

• 한국컴퓨터정보학회논문지
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• 제22권11호
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• pp.161-168
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• 2017

In this paper, we propose a Software Education Program for the Education Welfare Priority Support students. Elementary school students of education welfare priority support programs has low school satisfaction level and course maturity. Also, they have various problem such as relatively large digital divide when compared to general student. To solve such problem, we designed, developed, and applied a software education program on education welfare priority support program's elementary school students to analyze its effect on their learning motivation, self-efficacy, and goal orientation. Software education program followed the main stages of ADDIE model and was designed into experience Sharing, Requirements analysis, Sharing, Grouping, and Organizing. 20 of 6th graders in education welfare priority support programs were chosen as subject for software education program. The effectiveness has been analyzed through pre, and pro test. As a result of the analysis, we found that the developed software education program has meaningful effect on Learning Motivation, Self-efficacy, and Goal Orientation of education welfare priority support program's elementary students.

• 한국신뢰성학회지:신뢰성응용연구
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• 제17권4호
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• pp.296-304
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• 2017

Purpose: Recent weapon systems in defense have increased the complexity and importance of software when developing multifunctional equipment. In this study, we analyze the accuracy of the proposed software reliability model when applied to weapon systems. Methods: Determine the similarity between software reliability analysis results (prediction/estimation) utilizing data from developing weapon systems and system failures data during operation of weapon systems. Results: In case of a software reliability prediction model, the predicted failure rate was higher than the actual failure rate, and the estimation model was consistent with actual failure history data. Conclusion: The software prediction model needs to adjust the variables that are appropriate for the domestic weapon system environment. As the reliability of software is increasingly important in the defense industry, continuous efforts are needed to ensure accurate reliability analysis in the development of weapon systems.

• Asia pacific journal of information systems
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• 제23권1호
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• pp.1-19
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• 2013

The market for commercial open source software (OSS) has been rapidly growing with the proliferation of OSS. One way to commercialize OSS is the support model, which has been adopted by leading OSS firms such as Red Hat and JBoss. Despite the growing interest in OSS commercialization, little research has provided OSS support providers with a pricing guideline. In this paper, we examine the optimal pricing strategies for OSS support providers. Our benchmark is a monopoly case in which we investigate a startup software vendor's incentive to choose the OSS support regime over the proprietary one. Then we extend the model to a duopoly case in which OSS under the support regime competes against proprietary software. We characterize the conditions under which the OSS support model is viable under competition. We believe that our results offer insights to the OSS vendors who consider commercializing their OSS with a support model.

• 한국IT서비스학회지
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• 제8권4호
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• pp.129-140
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• 2009

The accurate estimation of software reliability is important to a successful development in software engineering. Until recent days, the models using regression analysis based on statistical algorithm and machine learning method have been used. However, this paper estimates the software reliability using support vector regression, a sort of machine learning technique. Also, it finds the best set of optimized parameters applying immune algorithm, changing the number of generations, memory cells, and allele. The proposed IA-SVR model outperforms some recent results reported in the literature.

• 한국산학기술학회논문지
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• 제15권9호
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• pp.5726-5737
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• 2014

무기체계에서의 소프트웨어에 대한 비중이 커짐에 따라, 소프트웨어 ILS(Integrated Logistics Support)에 대한 관심이 커지고 있다. 그러나 기존 무기체계에서 ILS 개발은 하드웨어 중심으로 적용하고 있어 소프트웨어에 그대로 적용하기 힘든 실정이다. 본 논문은 소프트웨어 ILS의 실무 적용 어려움이 무엇인지 원인을 파악하고 문제점을 분석하기 위해 국내/외 규정 및 사례들을 통해 현 실태를 파악하였다. 또한, 소프트웨어의 유지보수 특성을 고려하여 소프트웨어와 하드웨어 ILS의 차이점을 검토하고, 소프트웨어 ILS 요소개발 범위 설정을 통해 국내에 적용이 가능한 소프트웨어 ILS 개발방안을 제안하였다. 이는 소프트웨어 ILS 개발을 위한 구체적인 실무 적용방안을 수립하는 데 도움이 될 것으로 기대한다.

• 경영과학
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• 제23권2호
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• pp.75-91
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• 2006

The purpose of this paper is to propose a new software development cost estimation method using SVR(Support Vector Regression) SVR, one of machine learning techniques, has been attracting much attention for its theoretic clearness and food performance over other machine learning techniques. This paper may be the first study in which SVR is applied to the field of software cost estimation. To derive the new method, we analyze historical cost data including both well-known overseas and domestic software projects, and define cost drivers affecting software cost. Then, the SVR model is trained using the historical data and its estimation accuracy is compared with that of the linear regression model. Experimental results show that the SVR model produces more accurate prediction than the linear regression model.

• 문화기술의 융합
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• 제10권3호
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• pp.279-288
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• 2024

ICT의 발달과 함께 기업에서는 정보교환 또는 운영관리를 위해 소프트웨어를 필수적으로 사용하게 되었다. 그러나 ICT의 발달과 함께 증가한 보안 및 소프트웨어 관리이슈는 지속해서 해결해나가야 할 문제이다. 2021년 미국에서는 이러한 소프트웨어 보안 대응책 중 하나로 SBOM을 정부주도하에 표준화 및 제도를 수립하였다. 본 연구는 이러한 SBOM이 국내에 도입되기 위한 초석을 마련하는 연구로서 시작되었다. SBOM의 대표적인 특징들이 도입 의도에 미치는 영향을 바탕으로 경영층 지원과 제도적 지원을 조절 변수로 검증하였다. 그 결과, 경영층 지원으로는 보안관리가 유의미한 조절 변수로 나타났으며, 정부의 제도적 지원에서는 투명성이 유의미한 조절 변수로 나타났다. SBOM을 도입하기 위해서는 기업과 정부의 노력이 함께 이루어져야 하는데, 각 관점에서 중요하게 여기는 변수가 다르다는 것을 검증한 것이다. 본 연구가 SBOM의 발전과 도입에 기여하길 바라는 바이다.

• 한국지능시스템학회논문지
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• 제13권4호
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• pp.486-490
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• 2003

Software qualify models can predict the risk of faults in the software early enough for cost-effective prevention of problems. This paper introduces a least squares support vector machine (LS-SVM) as a fuzzy regression method for predicting fault ranges in the software under development. This LS-SVM deals with the fuzzy data with crisp inputs and fuzzy output. Predicting the exact number of bugs in software is often not necessary. This LS-SVM can predict the interval that the number of faults of the program at each session falls into with a certain possibility. A case study on software reliability problem is used to illustrate the usefulness of this LS -SVM.