The risk analysis of software projects based on Bayesian Network

Abstract

With the improvingof software technology and the level of project management, the success of software project is not a special case. But this does not mean that software project can be finished easily. In fact, The success ratio of software project is still low. The existing of Software system aim to reducej the uncertainty of practical system, but the process of itself is full of uncertainty. So it is essential to identify and analyze the software risk. Now lots of researches focus on the software project risk analysis, which apply a number of qualitative methods and quantitative methods. But most of methods ignore the dynamic nature of software project, only paying attention to predict in advance or analyze afterwards, which cannot meet the challenge of sorgware project management. So Bayesian network which canprovide real-time analysis is selected to analyze the software project risks. Through literature review and investigation of Chinese software professionals, the paper finds out 12 risk factors. In terms of an ERP project, revising above-mentioned risk factors, according to easy expansibility of topological structure and strong self-learning ability of Bayesian network, the paper uses priori knowledge and posterior knowledge to analyze the risk of the ERP project requirment period. Actual application shows that Bayesian network provide an effective system method for software project risk analysis.