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基于UML的软件度量 被引量:1

Software Metric Based on UML
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摘要 针对现有软件度量估算困难、精确度不高的问题,在预测性对象点基础上改进并提出基于UML的软件度量方法,可以从用例、序列图、类图度量软件。结果证明,与预测性对象点相比,该方法的精度提高了5%左右,其子系统偏差方向一致。 This paper improves predictive object points method and proposes a UML based metric to solve the problems of software estimation accuracy. Case model, sequence diagram and class diagram can be used to get software metric. The result proves this method's precision increases by 5% compared with predictive object points, and subsystems have same deviation direction.
作者 董琳
出处 《计算机工程》 CAS CSCD 北大核心 2008年第22期55-56,共2页 Computer Engineering
关键词 软件度量 软件工程 统一建模语言 预测性对象点 software metric software engineering UML predictive object points
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参考文献6

  • 1顾勋梅,宋国新,邵志清.一种改进的功能点分析方法[J].计算机工程,2007,33(22):12-14. 被引量:7
  • 2Chidamber S R, Kemerer C F. A Metrics Suite for Object Oriented Design[J]. IEEE Transactions on Software Engineering, 1994, 20(6): 476-493.
  • 3Lorenz M, Kidd J. Object-oriented Software Metrics[M]. [S.l.]: Prentice-Hall, 1994.
  • 4Whitmire S A. An Introduction to 3D Function Points[J]. Software Development, 1995, 3(4): 43-53.
  • 5Minkiewicz A. Measuring Object-oriented Software with Predictive Object Points[C]//Proc. of ASM'97. Atlanta, USA: [s. n.], 1997-10.
  • 6Carbone M, Santucci G. Fast & Serious: A UML Based Metric for Effort Estimation[C]//Proc. of the 6th ECOOP Workshop on Quantitative Approaches in Object-oriented Software Engineering. Malaga, Spain: [s. n.], 2002.

二级参考文献3

  • 1IFPUG.Function Point Counting Practices Manual,Release 4.1[Z].International Function Point Users Group,1999.
  • 2Abran A,Silva I,Primera L.Fields Studies Using Functional Size Measurement in Building Estimation Models for Software Maintenance[J].Journal of Software Maintenance and Evolution:Research and Practice,2002,14(1):31-64.
  • 3吴际,汤铭端.扩展功能点[J].软件学报,2001,12(2):309-316. 被引量:7

共引文献6

同被引文献11

  • 1王悠,罗燕京,易福华,房芳.基于用例的软件复杂度估算及应用[J].计算机技术与发展,2007,17(7):196-199. 被引量:3
  • 2李兴国,舒艳华,李嘉.基于支持向量机的软件可靠性早期预测[J].合肥工业大学学报(自然科学版),2007,30(7):859-863. 被引量:4
  • 3Zimmermann T,Nagappan N,Gall H,et al.Cross-project defect prediction:a large scale experiment on data vs.domain vs.process[C] //In:ESEC/FSE 2009.Amsterdam:ACM,2009:91-100.
  • 4Ostrand T J,Weyuker E J,Bell R M.Automating algorithms for the identification of fault-prone files[C] //In:Proceedings of the 2007 international symposium on Software testing and analysis.London,United Kingdom:ACM,2007:219-227.
  • 5Xing F,Guo P,Lyu M R.A novel method for early software quality prediction based on support vector machine[C] //In:Proceedings of the 16th IEEE International Symposium on Software Reliability Engineering.Citeseer:[s.n.] ,2005:213-222.
  • 6Schlkopf B,Smola A J,Williamson R C,et al.New Support Vector Algorithms[J].Neural Computation,2000,12(5):1207-1245.
  • 7姚王.基于UML的需求分析模型和设计模型的度量研究[D].合肥:合肥工业大学,2006.
  • 8Chidamber S R,Kemerer C F.A metrics suite for object oriented design[J].IEEE Transactions on Software Engineering,1994,20(6):476-493.
  • 9Zimmermann T,Premraj R,Zeller A.Predicting defects for eclipse[C] //In:ICSE 2007 Workshops,PROMISE'07.[s.l.] :[s.n.] ,2007.
  • 10Chalimourda A,Schlkopf B,Smola A J.Experimentally optimal ν in support vector regression for different noise models and parameter settings[J].Neural Networks,2004,17(1):127-141.

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