Risk Analysis Of Software Project Based On Bayesian Network

As a product that enters into enterprise customers and solves the supply chain problems,JD Group has high expectations for R project.However,due to the wide coverage of the functions involved,the system design becomes very complex,and a large number of new technologies are introduced.As a software project mainly based on R&D technology,how to effectively control risks is the focus of the project.Whether the project succeeds or not determines the success or failure of JD Group to enter the enterprise market.There are many shortcomings in the application of traditional risk management methods in software projects.For example,how to better assess the dependence between identified risks in a project;how much influence do they have on each other;and whether the same risk factor at different time points will be the incentive for other risks?These problems do not have effective analytical means.This paper takes R project of JD Group as an example,and combines Bayesian network model with risk analysis and control on the basis of traditional risk management methods.Through questionnaires to obtain the scope and extent of risk factors,through the combination of static model and dynamic model to analyze the impact of project risk factors in different time segments,to find out the relationship and dependence between risk factors.The problems arising from the interdependence of risk factors can be effectively controlled.The risk analysis model studied in this paper can provide a new analysis method for software projects.Through the application of the model in the project,the failure of risk control can be solved to a certain extent due to the unknown risk dependence.It can provide reference for risk management of similar software projects.