Software project risk analysis using Bayesian networks with causality constraints
Software project risk analysis using Bayesian networks with causality constraints
复制标题
使用具有因果约束的贝叶斯网络进行软件项目风险分析
DOI：
10.1016/j.dss.2012.11.001
复制
发表时间：
2013-12-01
影响因子：
7.5
通讯作者：
Liu, Mei
中科院分区：
文献类型：
--
作者：
Hu, Yong;Zhang, Xiangzhou;Liu, Mei
软件开发涉及许多风险，风险管理已成为软件开发中的关键活动之一。贝叶斯网络（BNS）已被探索为各种风险管理实践的工具，包括软件开发项目的风险管理。但是，有关软件风险分析的许多研究都集中在寻找风险因素与项目结果之间的相关性。软件项目失败通常是由于风险管理不足和无效的结果。为了获得适当有效的风险控制，应根据风险因果关系进行风险计划，这可以为决策提供更多风险信息。在这项研究中，我们建议使用具有因果关系约束（BNCC）的BNS进行软件开发项目的风险分析的模型。通过从302个收集的软件项目数据中学习的无限制自动因果关系，我们证明了所提出的模型不仅可以根据专家知识发现因果关系，而且在预测方面的表现比其他算法更好，例如Logistic Remistion，例如Logistic Remission，Naive Bayes，Naive Bayes，和一般BNS。这项研究介绍了软件项目风险因果关系分析的第一个因果发现框架，并使用BNCC在软件项目风险管理中应用了模型。 （c）2012 Elsevier B.V.保留所有权利。
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, Naive 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. (C) 2012 Elsevier B.V. All rights reserved.