Fuzzy Inference System-based Software Risk Assessment

The risk management is a very essential part in Software project management. However, due to the lack of enough understanding, many organizations neglect the software project risk management. Comparing to the normal projects, there are much more uncertainty in software projects.Software risk management includes risk assessment and risk control. Currently, risk assessment models are mainly from managers' experience. They directly predict the risk of software projects. The defect of such model used to be a large scale, or even complete intuition, so it's often subject to wrong and deficient of external data's support. So, how to make full use of measure systems to reduce subjectivity of risk assessment becomes an urgent problem to solve. In software risk management environment, we can assess the key parameters to achieve the goal. The uncertainties associated with parameter estimation results in inherent project risks. The identification and quantification of project risks associated with parameter estimation requires analytical tools that are effective and usable in project planning and control.A review of risk assessment methods reveals the need for additional methods to assess risk key parameters. Fuzzy set theory is a branch of mathematics that is useful for solving problems when only vague, subjective or imprecise information is available. A risk model was developed using fuzzy set theory. The risk model was tested using a sample subway management system. The results obtained from the model proved that a practical approach incorporating subject-matter expert assessment and fuzzy set theory could be used to assess software risk. Outputs from the model had sufficient fidelity for decision-makers to determine areas for additional control.