SIS Framework for Risk Assessment Through Quantitative Analysis

  • Abstract
  • Keywords
  • References
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  • Abstract

    Now a days, risk management plays very important role in Information systems, currently there are various risk assessment techniques. When system is analysing the source code, automatically some disputes may arise which depends on various reasons. These disputes may arise some of the risks in information system which may leads to loss of some data. To avoid that, in this paper we are implementing a framework for source code analysis which is used for brief assessment of risk, which includes guidance to risk minimization. In this framework source based risk assessment is done through the source code analysis. In order to assess risk that arose from the source code, first we need to calculate complexity of a source code in Information System. Finally the complexity which is the result of this framework will indicates the risk intensity of the source code.



  • Keywords

    Risk Assessment, Risk Management, Source code analysis, Effort or Performance.

  • References

      [1] Kutay, C. and Babar, M. A. 2005. Teaching three quality assur-ance techniques in tandem-lessons learned. In Fifth International Conference on Quality Software.QSIC’05. IEEE, 307–312

      [2] Risks Armen Keshishian1, Hasan Rashidi21Computer science Dept, Qazvin Azad UniversityIran, Tehran 2Hasan Rashidi, Qazvin Azad UniversityIran, Tehran

      [3] Arie van Deursen CWI and Delft University of Technolo-gy ,The Netherlands and Tobias Kuipers, Software Improvement Group ,The Netherlands

      [4] W. Eric Wong, Yu Qi, and Kendra Cooper Department of Com-puter Science University of Texas at Dallas Richardson, TX 75083 {ewong, yxq014100, kcooper}

      [5] J. Kontio, “The riskit method for software risk management”, Institute for Advanced Computer Studies and Department of Com-puter science, University of Maryland, 1999.

      [6] Lapierre, Sebastien, Lague, Bruno and Leduc, Charles. “Datrix Source Code Model and its Interchange Format: Lessons Learned and Considerations for Future Work. Montreal”, Canada: Bell Can-ada, Quality Engineering and Research, 2002.

      [7] Lyu, M., Yu, J., Keramidas, E. and Dalal, S. ARMOR:Analyzer for Reducing Module Operational Risk. In Proceedings of the Twenty-Fifth International Symposium on Fault-Tolerant Compu-ting (Pasadena, California, June 1995). IEEE Computer Society, Washington, DC, 137-142.








Article ID: 15715
DOI: 10.14419/ijet.v7i2.32.15715

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