Study on Predictor Measurement for Risk Management in Financial Information System
作者： TaeHong Kang , SungYul Rhew
DOI: 10.1007/978-3-642-32692-9_79
关键词: Actuarial science 、 Financial information 、 Index (economics) 、 System risk 、 Volume (computing) 、 Computer science 、 After treatment 、 Risk management 、 Information system 、 Computer security
摘要: Financial information system is a nationally and socially important infrastructure, thus risks in such infrastructures constitutes threat to both the nation society. However, current financial risk management feeble due lack of research its focus on after treatment rather than prevention. To increase prevention defects, measurement predictors that predict failures faults utmost importance. This paper established hypotheses evaluated market factors cause errors defects as trading volume, index fluctuation, number public announcements, orders fills, changing duties. It was shown duties caused while other showed no influence.
springer.com
sci-hub.st 参考文章(11)
Felix Salfner, Miroslaw Malek, Günther A. Hoffmann, Advanced Failure Prediction in Complex Software Systems Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, Institut für Informatik. ,(2004) , 10.18452/2500
Le Truong Giang, Dongwon Kang, Doo-Hwan Bae, Software Fault Prediction Models for Web Applications 2010 IEEE 34th Annual Computer Software and Applications Conference Workshops. pp. 51- 56 ,(2010) , 10.1109/COMPSACW.2010.19
Yuming Zhou, Hareton Leung, Empirical Analysis of Object-Oriented Design Metrics for Predicting High and Low Severity Faults IEEE Transactions on Software Engineering. ,vol. 32, pp. 771- 789 ,(2006) , 10.1109/TSE.2006.102
A.G. Koru, Hongfang Liu, Building effective defect-prediction models in practice IEEE Software. ,vol. 22, pp. 23- 29 ,(2005) , 10.1109/MS.2005.149
A.P. Nikora, J.C. Munson, Developing fault predictors for evolving software systems ieee international software metrics symposium. pp. 338- 350 ,(2003) , 10.1109/METRIC.2003.1232479
J.-J. Gras, End-to-end defect modeling IEEE Software. ,vol. 21, pp. 98- 100 ,(2004) , 10.1109/MS.2004.1331312
T.L. Graves, A.F. Karr, J.S. Marron, H. Siy, Predicting fault incidence using software change history IEEE Transactions on Software Engineering. ,vol. 26, pp. 653- 661 ,(2000) , 10.1109/32.859533
T. Hall, S. Beecham, D. Bowes, D. Gray, S. Counsell, A Systematic Literature Review on Fault Prediction Performance in Software Engineering IEEE Transactions on Software Engineering. ,vol. 38, pp. 1276- 1304 ,(2012) , 10.1109/TSE.2011.103
Ahmed E. Hassan, Predicting faults using the complexity of code changes international conference on software engineering. pp. 78- 88 ,(2009) , 10.1109/ICSE.2009.5070510
Norman E. Fenton, Martin Neil, Software metrics: roadmap international conference on software engineering. pp. 357- 370 ,(2000) , 10.1145/336512.336588