Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/14517
Title: Software project risk analysis using Bayesian networks with causality constraints
Authors: Hu, Y
Zhang, X
Ngai, EWT 
Cai, R
Liu, M
Keywords: Bayesian networks
Causality analysis
Expert knowledge constraint
Knowledge discovery
Software project risk analysis
Issue Date: 2012
Publisher: Elsevier
Journal: Decision support systems 
Abstract: 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. 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, Naïve Bayes, and general BNs. 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.
URI: http://hdl.handle.net/10397/14517
ISSN: 0167-9236
EISSN: 1873-5797
DOI: 10.1016/j.dss.2012.11.001
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

50
Last Week
1
Last month
1
Citations as of Oct 8, 2017

WEB OF SCIENCETM
Citations

35
Last Week
0
Last month
3
Citations as of Oct 15, 2017

Page view(s)

41
Last Week
1
Last month
Checked on Oct 15, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.