基于贝叶斯网络的软件风险管理问题的研究
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摘要
随着软件系统需求的不断增长，软件界的问题也越来越多，导致项目延期，超出预算或品质低劣的问题，被业内人士称之为“软件危机”。在软件项目开发过程中，风险是时时存在的。因此，如何确定风险内容，评价、度量风险的大小，制定补偿措施，将风险减至最小或可以接受的水平，是一个急待解决的问题。
本文在分析了SEI提出的软件风险管理的五步经典模型(风险识别，风险分析，风险计划，风险跟踪，和风险应对)之后，对该模型进行简化，使之成为风险识别，风险评价，风险对策，风险反应控制的四步模型；然后将重点放在简化模型中最重要的风险评价过程，提出将贝叶斯网络引入软件风险的定量分析中，利用贝叶斯网络的预测能力对风险发生概率进行预估。本文根据在实际工程中积累的专家经验，利用贝叶斯网络建立了风险预测局部模型，以及在软件开发周期的需求分析阶段和设计阶段的综合模型。最后结合模型给出利用贝叶斯网络进行定量风险分析的全过程，并用实例证明该风险模型的有效性。
The risk management is a very essential part in Software project management. However, due to the lack of enough understanding, many organizations neglect the software project risk management.
Firstly, this article introduces the typical theory about risk management and the typical risk management model, which is simplified for the real problem later.
The main problems in software risk management are pointed out. The limitations of existing management methods to handle these problems are analyzed, an method using Bayesian networks to conduct risk prediction is presented, and the local and synthetic models are individually given. The algorithms are given to deal with situations when the new evidences are captured.
An application example shows that this method is effective to predict the risk probabilities during the specification and design phases of the project.
本文在分析了SEI提出的软件风险管理的五步经典模型(风险识别，风险分析，风险计划，风险跟踪，和风险应对)之后，对该模型进行简化，使之成为风险识别，风险评价，风险对策，风险反应控制的四步模型；然后将重点放在简化模型中最重要的风险评价过程，提出将贝叶斯网络引入软件风险的定量分析中，利用贝叶斯网络的预测能力对风险发生概率进行预估。本文根据在实际工程中积累的专家经验，利用贝叶斯网络建立了风险预测局部模型，以及在软件开发周期的需求分析阶段和设计阶段的综合模型。最后结合模型给出利用贝叶斯网络进行定量风险分析的全过程，并用实例证明该风险模型的有效性。
The risk management is a very essential part in Software project management. However, due to the lack of enough understanding, many organizations neglect the software project risk management.
Firstly, this article introduces the typical theory about risk management and the typical risk management model, which is simplified for the real problem later.
The main problems in software risk management are pointed out. The limitations of existing management methods to handle these problems are analyzed, an method using Bayesian networks to conduct risk prediction is presented, and the local and synthetic models are individually given. The algorithms are given to deal with situations when the new evidences are captured.
An application example shows that this method is effective to predict the risk probabilities during the specification and design phases of the project.
引文
1．Elaine M.Hall著，王海鹏 周靖译，风险管理——软件系统开发方法，第一版，北京：清华大学出版社，2002
2．王军，周伟达，贝叶斯网络的研究与进展，电子科技，1999，697～714
3．王青 基于ISO9000&CMM的软件质量保证模型 中国科学院软件研究所
4．徐宾刚、屈梁生、陶肖明，转子故障贝叶斯诊断网络的研究，机械工程学报，2004，40(1)66～73
5．李伟生、王宝树，基于贝叶斯网络的态势评估，系统工程与电子技术，2003，25(4)：480～484
6．王辉，用于决策支持的贝叶斯网络，东北师大学报自然科学版，2001，33(4)：26～31
7．王辉，用于预测的贝叶斯网络，东北师大学报自然科学版，2002，34(1)：10～16
8．詹原瑞、谢秋平、李雪，贝叶斯网络在因果图中的应用，管理工程学报，2003，17(2)：118～122
9．胡兆勇、屈梁生，一种贝叶斯诊断网络的拓扑结构，2003，37(11)：1115～1119
10．李俭川、胡茑庆、秦国军、温熙森，贝叶斯网络理论及其在设备故障诊断中的应用，中国机械工程，2003，14(10)：896～901
11．李俭川、胡茑庆、秦国军、温熙森，基于贝叶斯网络的故障诊断策略优化方法，2003，18(5)：568～573
12．程岳、王宝树、李伟生，贝叶斯网络在态势估计中的应用，计算机工程与应用，2002，23：206～210
13．霍利民、朱永利、苏海锋，基于贝叶斯网络的配电系统可靠性分析方法，2003，30(6)：7～12
14．邹丰忠、徐仁佐，软件可靠性多模型综合评估，同济大学学报，2002，30(10)：1183～1185
15．李俭川、胡茑庆、秦国军、温熙森，基于故障树的贝叶斯网络建造方法与故障诊断应用，计算机工程与应用，2003．24：225～229
16．杨立群，软件开发项目失败的原因，中国计算机报，2001．11
17. Shachter R D. Probalilistic Inference and Influence Diagrams. Operations Research, 1988,36(4):589～605
18. Coper G F. The Computational Complexity of Probabilistic Inference Using Bayesian Belief Networks, Artificial Intelligence, 1990,42(2-3): 393～405
19. Mark C. Paulk, Bill Curtis, Mary Beth Chrissis, Charles V. Weber, Capability Maturity Model SM for Software, Version 1.1 Pearl J., Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference, San Mateo, CA, Morgan Ksufmann, 1988
20. Humphrey W. A Discipline for Software Engineering. Reading, MA:Addison-Wesley, 1995
21. H. Ammar, T. Nikzadeh, and J.B. Dugan, "Risk assessment of software-system specifications," IEEE Transactions on Reliability, vol. 50, no. 2, pp. 171-183, June 2001.
22. Charniak E, Bayesian Networks without Tears, AI Magazine, 1992,12(4):50～63
23. Pearl J, Graphical Models for Probabilistic and Causal Reasoning, In:The Computer Science and Engineering Handbook, Kluwer Academic Publishers, 1997:697～714
24. Michael L Raymer et al, Dimensionality Reduction Using Cenetic Algorithms[J]. IEEE Trans on Evolutionary compution, 2002:4(2):164～171
25. A. Mockus, R.T. Fielding, and J. Herbsleb, "A case study of open source software development: the apache server," in Proceedings of the 22nd International Conference on Software Engineering, 2000.
26. G. Denaro and M. Pezz'e, "An empirical evaluation of fault-proneness models," in Proceedings of the 24th International Conference on Software Engineering, May 2002.
27．Wallmueller,Ernest．《软件质量保证的实践方法》Prentice Hall, Inc 1994. ISBN 0-13-819780-6
28．Schulmeyer，G Gordon《零过失错误软件》．McGraw-Hill，Inc．1990．ISBN 0-07-055663-6
29．Glass, Robert.《构造软件质量》．Prentice-Hall, Inc. 1992. ISBN 0-13-086695-4
30．Boogaard, Martin. 《在信息系统的适应性中通过数据无关性减少软件错误》．Thesis Publishers, Amsterdam, 1994. ISBN 90-5170-289-2
31. Curran, E. and Sanders, J.《软件质量：软件开发和支持的成功框架》．Addison-Wesley Publishing Co., Inc. 1994, ISBN 0-201-63198-9
32. Vidgen, R. T. and Wood-Harper, A. T.,《确定和管理质量的有关概念》，从《软件质量管理，》扩展。Elsevier Science Publishers, London. 1993 ISBN 1-85166-963-9
33. M. Stamatelatos et al., "Probabilistic risk assessment procedures guide for NASA managers and practitioners," Technical Report ver 1.1, NASA Office of Safety and Mission Assurance, Aug. 2002. Project Management Institution, Inc. A Guide to the Project Management Body of Knowledge, ISBN: 1-880410-23-0
34. B. A. Gran and A. Helminen, "A bayesian belief network for reliability assessment," in Proceedings of the 20th SAFECOMP, 2001.
35. C. Smidts, R. Stoddard, and M. Stutzke, "Software reliability modeling: An approach to early reliability prediction," IEEE Transactions on Reliability, vol. 47, no. 3, pp. 268-278, 1998.
36. F. Padberg, "Empirical interval estimates for the defect content after an inspection," in Proceedings of ICSE, May 2002.
37. N. E. Fenton and N. Ohlsson, "Quantitative analysis of faults and failures in a complex software system," IEEE Transactions on Software Engineering, vol. 26, no. 8, pp. 797-814, 2000.
38. Khaled El Emam et al., "The optimal class size for object-oriented software," IEEE Transactions on Software Engineering, vol. 28, no. 5, pp. 494-509, May 2002.
39. Dan Houston, Ph. D. candidate, Arizona State University, Results of Survey on Potential Effects of Major Software Development Risk Factors http://www.eas.asu.edu/～sdm/dhouston/risksrvy.htm
40．田竣国，软件项目规模估计方 htttp://www.chinabyte.net/20030220/1653068.shtml
41．陈兵，软件开发质量和风险的定量监督 http://www.sawin.com.cn/doc/SE/SPI/psuoervise2.htm
42．廖波，CMM与软件评价及其测试 http://www.sawin.com.cn/doc/OM/CMM/cmmtest.htm
43．Adams Wang，功能点过程 http://www.sawin.com.cn/doc/QM/SCM/functionpoint.htm
44．北京旋极信息技术有限公司软件测试中心，软件复杂度概述 http://www.watertek.com/chanpin/ceshi/002.htm
45．徐瑞恩，深入讨论软件成熟度模型 http://www.sawin.com.cn/doc/OM/CMM/deepcmm.htm
46．何云，项目管理中风险评价的必要性 http://www.51cmm.com/ProjectManage/No095.htm
47．张蓬，如何建立复杂项目的WBS结构 http://www.51cmm.com/ProjectManage/No141.htm
48．何云，软件系统安全性风险评价 http://www.51cmm.com/ProjectManage/No107.htm
2．王军，周伟达，贝叶斯网络的研究与进展，电子科技，1999，697～714
3．王青 基于ISO9000&CMM的软件质量保证模型 中国科学院软件研究所
4．徐宾刚、屈梁生、陶肖明，转子故障贝叶斯诊断网络的研究，机械工程学报，2004，40(1)66～73
5．李伟生、王宝树，基于贝叶斯网络的态势评估，系统工程与电子技术，2003，25(4)：480～484
6．王辉，用于决策支持的贝叶斯网络，东北师大学报自然科学版，2001，33(4)：26～31
7．王辉，用于预测的贝叶斯网络，东北师大学报自然科学版，2002，34(1)：10～16
8．詹原瑞、谢秋平、李雪，贝叶斯网络在因果图中的应用，管理工程学报，2003，17(2)：118～122
9．胡兆勇、屈梁生，一种贝叶斯诊断网络的拓扑结构，2003，37(11)：1115～1119
10．李俭川、胡茑庆、秦国军、温熙森，贝叶斯网络理论及其在设备故障诊断中的应用，中国机械工程，2003，14(10)：896～901
11．李俭川、胡茑庆、秦国军、温熙森，基于贝叶斯网络的故障诊断策略优化方法，2003，18(5)：568～573
12．程岳、王宝树、李伟生，贝叶斯网络在态势估计中的应用，计算机工程与应用，2002，23：206～210
13．霍利民、朱永利、苏海锋，基于贝叶斯网络的配电系统可靠性分析方法，2003，30(6)：7～12
14．邹丰忠、徐仁佐，软件可靠性多模型综合评估，同济大学学报，2002，30(10)：1183～1185
15．李俭川、胡茑庆、秦国军、温熙森，基于故障树的贝叶斯网络建造方法与故障诊断应用，计算机工程与应用，2003．24：225～229
16．杨立群，软件开发项目失败的原因，中国计算机报，2001．11
17. Shachter R D. Probalilistic Inference and Influence Diagrams. Operations Research, 1988,36(4):589～605
18. Coper G F. The Computational Complexity of Probabilistic Inference Using Bayesian Belief Networks, Artificial Intelligence, 1990,42(2-3): 393～405
19. Mark C. Paulk, Bill Curtis, Mary Beth Chrissis, Charles V. Weber, Capability Maturity Model SM for Software, Version 1.1 Pearl J., Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference, San Mateo, CA, Morgan Ksufmann, 1988
20. Humphrey W. A Discipline for Software Engineering. Reading, MA:Addison-Wesley, 1995
21. H. Ammar, T. Nikzadeh, and J.B. Dugan, "Risk assessment of software-system specifications," IEEE Transactions on Reliability, vol. 50, no. 2, pp. 171-183, June 2001.
22. Charniak E, Bayesian Networks without Tears, AI Magazine, 1992,12(4):50～63
23. Pearl J, Graphical Models for Probabilistic and Causal Reasoning, In:The Computer Science and Engineering Handbook, Kluwer Academic Publishers, 1997:697～714
24. Michael L Raymer et al, Dimensionality Reduction Using Cenetic Algorithms[J]. IEEE Trans on Evolutionary compution, 2002:4(2):164～171
25. A. Mockus, R.T. Fielding, and J. Herbsleb, "A case study of open source software development: the apache server," in Proceedings of the 22nd International Conference on Software Engineering, 2000.
26. G. Denaro and M. Pezz'e, "An empirical evaluation of fault-proneness models," in Proceedings of the 24th International Conference on Software Engineering, May 2002.
27．Wallmueller,Ernest．《软件质量保证的实践方法》Prentice Hall, Inc 1994. ISBN 0-13-819780-6
28．Schulmeyer，G Gordon《零过失错误软件》．McGraw-Hill，Inc．1990．ISBN 0-07-055663-6
29．Glass, Robert.《构造软件质量》．Prentice-Hall, Inc. 1992. ISBN 0-13-086695-4
30．Boogaard, Martin. 《在信息系统的适应性中通过数据无关性减少软件错误》．Thesis Publishers, Amsterdam, 1994. ISBN 90-5170-289-2
31. Curran, E. and Sanders, J.《软件质量：软件开发和支持的成功框架》．Addison-Wesley Publishing Co., Inc. 1994, ISBN 0-201-63198-9
32. Vidgen, R. T. and Wood-Harper, A. T.,《确定和管理质量的有关概念》，从《软件质量管理，》扩展。Elsevier Science Publishers, London. 1993 ISBN 1-85166-963-9
33. M. Stamatelatos et al., "Probabilistic risk assessment procedures guide for NASA managers and practitioners," Technical Report ver 1.1, NASA Office of Safety and Mission Assurance, Aug. 2002. Project Management Institution, Inc. A Guide to the Project Management Body of Knowledge, ISBN: 1-880410-23-0
34. B. A. Gran and A. Helminen, "A bayesian belief network for reliability assessment," in Proceedings of the 20th SAFECOMP, 2001.
35. C. Smidts, R. Stoddard, and M. Stutzke, "Software reliability modeling: An approach to early reliability prediction," IEEE Transactions on Reliability, vol. 47, no. 3, pp. 268-278, 1998.
36. F. Padberg, "Empirical interval estimates for the defect content after an inspection," in Proceedings of ICSE, May 2002.
37. N. E. Fenton and N. Ohlsson, "Quantitative analysis of faults and failures in a complex software system," IEEE Transactions on Software Engineering, vol. 26, no. 8, pp. 797-814, 2000.
38. Khaled El Emam et al., "The optimal class size for object-oriented software," IEEE Transactions on Software Engineering, vol. 28, no. 5, pp. 494-509, May 2002.
39. Dan Houston, Ph. D. candidate, Arizona State University, Results of Survey on Potential Effects of Major Software Development Risk Factors http://www.eas.asu.edu/～sdm/dhouston/risksrvy.htm
40．田竣国，软件项目规模估计方 htttp://www.chinabyte.net/20030220/1653068.shtml
41．陈兵，软件开发质量和风险的定量监督 http://www.sawin.com.cn/doc/SE/SPI/psuoervise2.htm
42．廖波，CMM与软件评价及其测试 http://www.sawin.com.cn/doc/OM/CMM/cmmtest.htm
43．Adams Wang，功能点过程 http://www.sawin.com.cn/doc/QM/SCM/functionpoint.htm
44．北京旋极信息技术有限公司软件测试中心，软件复杂度概述 http://www.watertek.com/chanpin/ceshi/002.htm
45．徐瑞恩，深入讨论软件成熟度模型 http://www.sawin.com.cn/doc/OM/CMM/deepcmm.htm
46．何云，项目管理中风险评价的必要性 http://www.51cmm.com/ProjectManage/No095.htm
47．张蓬，如何建立复杂项目的WBS结构 http://www.51cmm.com/ProjectManage/No141.htm
48．何云，软件系统安全性风险评价 http://www.51cmm.com/ProjectManage/No107.htm