금융정보시스템의 장애관리를 위한 장애요인변수 추출에 관한 연구
Finance Information System is critical national infrastructure. Therefore it is important to select variables of defect causal factor for the system defect management effectively. We research and analyze detected errors in A Company's Finance Information System for three years. In the result of...
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          | Published in | 정보처리학회논문지. KIPS transactions on software and data engineering. 소프트웨어 및 데이터 공학 Vol. 2; no. 6; pp. 369 - 376 | 
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| Main Authors | , , , | 
| Format | Journal Article | 
| Language | Korean | 
| Published | 
          
        2013
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| Online Access | Get full text | 
| ISSN | 2287-5905 | 
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| Abstract | Finance Information System is critical national infrastructure. Therefore it is important to select variables of defect causal factor for the system defect management effectively. We research and analyze detected errors in A Company's Finance Information System for three years. In the result of research and analysis, we have selected 9 variables of defect factor: the trading volume, the fluctuation of KOSDAQ index, and the number of public announcements, etc. Then we have assumed that these variables affect real system errors and analyzed correlation between the hypothesis and the detected system errors. After analyzing, we have extracted the trading volume, the number of orders and fills, changing tasks, and the fluctuations of NASDAQ index as valid variables of defect factor. These variables are proposed for failure prediction model as the variables to manage defects in the finance information system afterward. 금융정보시스템은 국가나 사회의 중요한 인프라로서 실효성 있는 장애관리를 위해서는 장애요인변수의 선택이 매우 중요하다. 본 연구에서는 A사의 3년 간 금융정보시스템에서 발생한 장애를 조사 분석하였다. 조사 분석 결과, 거래량, KOSDAQ 지수의 등락, 공시건수 등 9개의 변수가 채택되어, 이 장애요인 변수들이 실제 장애를 유발한다는 가설을 세우고, 실제 발생한 장애와의 상관관계를 분석하였다. 분석 결과, 거래량, 주문/체결건수, 변경업무, 나스닥 지수의 등락이 유효한 장애요인 변수로서 채택되었다. 따라서 본 연구에서는 이 변수들을 금융정보시스템의 장애관리를 위한 장애모델변수로서 장애예측 모델에 활용할 수 있도록 제안한다. | 
    
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| AbstractList | Finance Information System is critical national infrastructure. Therefore it is important to select variables of defect causal factor for the system defect management effectively. We research and analyze detected errors in A Company's Finance Information System for three years. In the result of research and analysis, we have selected 9 variables of defect factor: the trading volume, the fluctuation of KOSDAQ index, and the number of public announcements, etc. Then we have assumed that these variables affect real system errors and analyzed correlation between the hypothesis and the detected system errors. After analyzing, we have extracted the trading volume, the number of orders and fills, changing tasks, and the fluctuations of NASDAQ index as valid variables of defect factor. These variables are proposed for failure prediction model as the variables to manage defects in the finance information system afterward. 금융정보시스템은 국가나 사회의 중요한 인프라로서 실효성 있는 장애관리를 위해서는 장애요인변수의 선택이 매우 중요하다. 본 연구에서는 A사의 3년 간 금융정보시스템에서 발생한 장애를 조사 분석하였다. 조사 분석 결과, 거래량, KOSDAQ 지수의 등락, 공시건수 등 9개의 변수가 채택되어, 이 장애요인 변수들이 실제 장애를 유발한다는 가설을 세우고, 실제 발생한 장애와의 상관관계를 분석하였다. 분석 결과, 거래량, 주문/체결건수, 변경업무, 나스닥 지수의 등락이 유효한 장애요인 변수로서 채택되었다. 따라서 본 연구에서는 이 변수들을 금융정보시스템의 장애관리를 위한 장애모델변수로서 장애예측 모델에 활용할 수 있도록 제안한다. | 
    
| Author | Rhew, Sung-Yul Kang, Tae-Hong 류성열 강태홍  | 
    
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| Title | 금융정보시스템의 장애관리를 위한 장애요인변수 추출에 관한 연구 | 
    
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