相关向量机软件可靠性建模中失效数据选择

杨小明; 楼俊钢; 沈张果; 胡文军

doi:10.11959/j.issn.1000-0801.2015192

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相关向量机软件可靠性建模中失效数据选择

研究与开发 | 更新时间：2024-06-05

- 相关向量机软件可靠性建模中失效数据选择
- Selection of Failure Data in Software Reliability Modeling Based on RVM
- 电信科学 2015年31卷第9期页码：90-96
- 作者机构：
  
  1. 湖州师范学院信息工程学院湖州313000
  2. 浙江大学控制科学与工程学系杭州310058
- 作者简介：
  
  [ "杨小明，男，湖州师范学院实验师、实验中心主任，主要研究方向为软件可靠性建模、大数据分析、可信计算等。" ]
  [ "楼俊钢，男，博士，湖州师范学院副教授、系主任，主要研究方向为软件可靠性建模、软件测试、大数据分析等。" ]
  [ "沈张果，男，湖州师范学院讲师，主要研究方向为大数据分析、软件可靠性建模、智能交通等。" ]
  [ "胡文军，男，博士，湖州师范学院副教授、副院长，主要研究方向为模式识别、人工智能等。" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61103051);浙江省自然科学基金资助项目;Natural Science Foundation of Zhejiang Province(LY15F020018);浙江省公益性技术应用研究计划基金资助项目;Zhejiang Provincial Science and Technology Plan of China(2015C33247)
- DOI：10.11959/j.issn.1000-0801.2015192
  中图分类号：
- 网络出版日期：2015-09，
  
  纸质出版日期：2015-09-20
- 稿件说明：
移动端阅览
杨小明, 楼俊钢, 沈张果, 等. 相关向量机软件可靠性建模中失效数据选择[J]. 电信科学, 2015,31(9):90-96.

Xiaoming Yang, Jungang Lou, Zhangguo Shen, et al. Selection of Failure Data in Software Reliability Modeling Based on RVM[J]. Telecommunications science, 2015, 31(9): 90-96.
杨小明, 楼俊钢, 沈张果, 等. 相关向量机软件可靠性建模中失效数据选择[J]. 电信科学, 2015,31(9):90-96. DOI： 10.11959/j.issn.1000-0801.2015192.

Xiaoming Yang, Jungang Lou, Zhangguo Shen, et al. Selection of Failure Data in Software Reliability Modeling Based on RVM[J]. Telecommunications science, 2015, 31(9): 90-96. DOI： 10.11959/j.issn.1000-0801.2015192.

摘要

摘要：基于核函数的软件可靠性模型一般对软件失效时间数据与发生在其之前的m次失效时间数据的关系进行建模，着重研究了m取值不同时，其对核函数可靠性模型预测能力的影响。在5个不同类型失效数据集上，采用Mann-Kendall检验观测到m值增大时模型预测能力逐渐下降，说明现时失效时间数据能比较久之前观测的失效时间数据更好地用于预测未来，通过把m的取值划分成几个区间，运用配对T检验进行实验研究，结果表明当m∈｛6

10｝时，模型能够得到最好的预测性能。

Abstract

The high complexity of software is the major contributing factor of software reliability problems

and traditional parametric models may exhibit different predictive capabilities among different software projects

it is hard to select a suitable model for every software projects. Compared to traditional models

kernel based models could achieve better prediction accuracy

and had arouse the interesting of many researchers. The RVM learning scheme was applied to model the failure time data so as to capture the inner correlation between software failure time data and the m nearest failure time data. In addition

the trend of predictive accuracy with the varying of m was detected by way of Mann-Kendall test method. Thereupon

the reasonable value range of m was achieved

thus m∈｛6

10｝ through paired T-test in 5 common used software failure data.

关键词

Keywords

references

IEEE Std 1633-2008. IEEE Recommended Practice on Software Reliability , 2008

Inoue S , Yamada S . Generalized discrete software reliability modeling with effect of program size . IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans , 2007 , 37 （ 2 ）: 170 ～ 179

Liu M X , Miao L , Zhang D Q . Two stage cost sensitive learning for software defect prediction . IEEE Transactions on Reliability , 2014 , 63 （ 2 ）: 676 ～ 686

李海峰，王栓奇，刘畅等．考虑测试工作量与覆盖率的软件可靠性模型．软件学报， 2013 , 24 （ 4 ）: 749 ～ 760

Li H F , Wang S Q , Liu C , et al . Software reliability model considering both testing effort and testing coverage . Journal of Software , 2013 , 24 （ 4 ）: 749 ～ 760

Peng W , Huang H Z , Xie M , et al . A Bayesian approach for system reliability analysis with multilevel pass fail, lifetime and degradation data sets . IEEE Transactions on Reliability , 2013 , 62 （ 3 ）: 689 ～ 699

陆文，徐锋，吕建．一种开放环境下的软件可靠性评估方法．计算机学报， 2010 , 33 （ 3 ）: 452 ～ 462

Lu W , Xu F , Lv J . An approach of software reliability evaluation in the open environment . Chinese Journal of Computers , 2010 , 33 （ 3 ）: 452 ～ 462

Sun Z B , Song Q B , Zhu X Y . Using coding based ensemble learning to improve software defect prediction . IEEE Transactions on Systems,Man,Cybernetics , 2012 , 42 （ 6 ）: 1806 ～ 1817

Chatzis S , Andreou A . Maximum entropy discrimination poisson regression for software reliability modeling . IEEE Transactions on Neural Networks and Learning , 2015 ,has been accepted by inclusion in a future issue

谢景燕，安金霞，朱纪洪．考虑不完美排错情况的NHPP类软件可靠性增长模型．软件学报， 2010 , 21 （ 5 ）: 942 ～ 949

Xie J Y , An J X , Zhu J H . NHPP software reliability growth model considering imperfect debugging . Journal of Software , 2010 , 21 （ 5 ）: 942 ～ 949

陆文，徐锋，吕建．一种开放环境下的软件可靠性评估方法．计算机学报， 2010 , 33 （ 3 ）: 452 ～ 462

Lu W , Xu F , Lv J . An Approach of Software Reliability Evaluation in the Open Environment . Chinese Journal of Computers , 2010 , 21 （ 5 ）: 452 ～ 462

Schneidewind N , Hinchey M . A complexity reliability model . Proceedings of 20th International Symposium on Software Reliability Engineering , Mysuru, India , 2009 : 1 ～ 10

Cotroneo D , Pietrantuono R , Russo S . Combining operational and debug testing for improving reliability . IEEE Transactions on Reliability , 2013 , 62 （ 2 ）: 408 ～ 423

Liu M X , Miao L , Zhang D Q . Two stage cost sensitive learning for software defect prediction . IEEE Transactions on Reliability , 2014 , 63 （ 2 ）: 676 ～ 686

Wayne M , Modarres M . A bayesian model for complex system reliability growth under arbitrary corrective actions . IEEE Transactions on Reliability , 2015 , 64 （ 1 ）: 206 ～ 220

Li X N , Mabu S , Hirasawa K . A novel graph based estimation of the distribution algorithm and its extension using reinforcement learning . IEEE Transactions on Evolutionary Computation , 2014 , 18 （ 1 ）: 98 ～ 113

Tian L , Noore A . Dynamic software reliability prediction: an approach based on support vector machines . International Journal of Reliability, Quality and Safety Engineering , 2005 , 12 （ 4 ）: 309 ～ 321

Xing F , Guo P , Lyu M R . A novel method for early software quality prediction based on support vector machines . Proceedings of International Symposium on Software Reliability Engineering （ISSRE'05） , Chicago, Illinois,USA , 2005 : 213 ～ 222

Yang B , Li X . A study on software reliability prediction based on support vector machines . Proceedings of IEEE International Conference on Industrial Engineering and Engineering Management , Singapore , 2007 : 1176 ～ 1180

Yuan F Q , UDAY K , MISRA K B . Complex system reliability evaluation using support vector machine for incomplete data-set . International Journal of Performability Engineering , 2011 , 7 （ 3 ）: 32 ～ 42

Park J , Lee N , Baik J . On the long-term predictive capability of data-driven software reliability model: an empirical evaluation . Proceedings of 25th International Symposium on Software Reliability Engineering , Naples , 2014 : 45 ～ 54

楼俊钢，蒋云良，申情等．软件可靠性预测中不同核函数的预测能力评估．计算机学报， 2013 , 33 （ 6 ）: 1303 ～ 1311

Lou J G , Jiang Y L , Shen Q , et al . Evaluating the prediction performance of different kernel functions in kernel based software reliability models . Chinese Journal of Computers , 2013 , 36 （ 6 ）: 1303 ～ 1311

Lou J G , Jiang J H , Shuai C Y . A study on software reliability prediction based on transduction inference . Proceedings of IEEE 19th Asian Test Symposium, Los Alamitos: IEEE Computer Society , Shanghai, China , 2010 : 77 ～ 80

Ohba M . Software reliability analysis models . IBM Journal of Research and Development , 1984 , 28 （ 4 ）: 428 ～ 443

Kendall M G . A new measure of rank correlation . Biometrical , 1938 , 30 （ 2 ）: 81 ～ 93

Douglas C D . Design and Analysis of Experiments , 6th Edition . New York: John Wiley ＆ Sons. Inc , 2007

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