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Findings from New Jersey Institute of Technology Broaden Understanding of Bayesian Analysis

February 6, 2014



By a News Reporter-Staff News Editor at Computer Weekly News -- Investigators publish new report on Bayesian Analysis. According to news reporting originating from Newark, New Jersey, by VerticalNews correspondents, research stated, "Many risks are involved in software development and risk management has become one of the key activities in software development. Bayesian networks (BNs) have been explored as a tool for various risk management practices, including the risk management of software development projects."

Our news editors obtained a quote from the research from the New Jersey Institute of Technology, "However, much of the present research on software risk analysis focuses on finding the correlation between risk factors and project outcome. Software project failures are often a result of insufficient and ineffective risk management. To obtain proper and effective risk control, risk planning should be performed based on risk causality which can provide more risk information for decision making. In this study, we propose a model using BNs with causality constraints (BNCC) for risk analysis of software development projects. Through unrestricted automatic causality learning from 302 collected software project data, we demonstrated that the proposed model can not only discover causalities in accordance with the expert knowledge but also perform better in prediction than other algorithms, such as logistic regression, C4.5, Naive Bayes, and general BNs."

According to the news editors, the research concluded: "This research presents the first causal discovery framework for risk causality analysis of software projects and develops a model using BNCC for application in software project risk management."

For more information on this research see: Software project risk analysis using Bayesian networks with causality constraints. Decision Support Systems, 2013;56():439-449. Decision Support Systems can be contacted at: Elsevier Science Bv, PO Box 211, 1000 Ae Amsterdam, Netherlands. (Elsevier - www.elsevier.com; Decision Support Systems - www.elsevier.com/wps/product/cws_home/505540)

The news editors report that additional information may be obtained by contacting Y. Hu, New Jersey Inst Technol, Dept. of Comp Sci, Newark, NJ 07102, United States. Additional authors for this research include X.Z. Zhang, E.W.T. Ngai, R.C. Cai and M. Liu.

Keywords for this news article include: Newark, Software, New Jersey, United States, Bayesian Analysis, Bayesian Networks, North and Central America

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Source: Computer Weekly News


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