본문 바로가기
KERD
논문KCI 등재

금융정보시스템의 장애관리를 위한 장애요인변수 추출에 관한 연구

A Study on Extraction of Defect Causal Variables for Defect Management in Financial Information System

0

조회

0

다운로드

1

인용

0

참고문헌

키워드

주제분류컴퓨터학

초록

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.

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.

참고문헌 (18)

  1. National IT Industry Promotion Agency, "SW Engineering White Book", pp.5~6 (2011), NIPA
  2. S.K. Oh, "Risk Management Theory" (1999), Kyungmoon Publishers
  3. H.S. Park, "Recent Domestic Bank’s Risk Management and Future Works", The Bank of Korea, Finance Systems Review, 7, pp.85~95 (2002)
  4. 강태홍, "금융정보시스템 위험관리의 현황 및 개선을 위한 제언", Information Systems Review, 14(2), pp.103~115 (2012), 한국경영정보학회
  5. Telecommunication Technology Association, "Information System Management Guides", TTA, ~ (2007)
  6. IEEE, "IEEE Std 1044-2009, Standard Classification for Software Anomalies", IEEE, ~ (2009)
  7. Todd L. Graves, "Predicting Fault Incidence Using Software Change History", IEEE Transactions on Software Engineering, 26(7) (2000)
  8. Allen P. Nikora, "Developing Fault Predictors for Evolving Software Systems", Proceedings of the 9th International Metrics Symposium(METRICS’03) (2003), IEEE
  9. Improved Software Defect Prediction, "Martin Neil", Agena Ltd and Queen Mary, University of London, ~ (2004)
  10. Jean Jacques Gras, "End-to-End Defect Modeling" (2004), IEEE Computer Society
  11. A. Gunes Kore, "Building Effective Defect-Prediction Models in Practice" (2005)
  12. Yuming Zhou, "Empirical Analysis of Object-Oriented Design Metrics for Predicting High and Low Severity Faults", IEEE Transactions on Software Engineering, 32(10) (2006)
  13. Pietro Abate, "Predicting Upgrade Failure Using Dependency Analysis" (2011), IEEE
  14. Tracy Hall, "Systematic Literature Review on Fault Prediction Performance in Software Engineering", IEEE Transactions of Software Engineering (2011)
  15. Gunther A. Hoffman, "Advanced Failure Prediction in Complex Software Systems" (2004), Humbolt Univ, Berlin, Dep of Computer Science, Computer Architecture and Communication Group
  16. Bibi S., "Software Defect Prediction Using Regression via Classification" (2006), IEEE
  17. Ahmed E. Hassan, "Predicting Faults Using the Complexity of Code Changes" (2009), IEEE
  18. Le Truong Giang, "Software Fault Prediction Models for Web Applications", 2010 34th Annual IEEE Computer Software and Applications Conference Workshops (2010)

관련 논문AI추천

이 간행물의 다른 논문 (7건)