Wuhan University Journal of Natural Sciences

, Volume 12, Issue 5, pp 927–931 | Cite as

Grey prediction based software stage-effort estimation

Article

Abstract

The software stage-effort estimation can be used to dynamically adjust software project schedule, further to help make the project finished on budget. This paper presents a grey model Verhulst based method for stage-effort estimation during software development process, a bias correction technology was used to improve the estimation accuracy. The proposed method was evaluated with a large-scale industrial software engineering database. The results are very encouraging and indicate the method has considerable potential.

Key words

project management software engineering sorftware effort estimation grey model 

CLC number

TP 311.5 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    Shepperd M J. Evaluating Software Project Prediction Systems[C]//11th IEEE International Software Metrics Symposium (METRICS 2005). Como, Italy, September 19–22, 2005.Google Scholar
  2. [2]
    Deng Julong. Control Problems of Grey Systems[J]. Systems & Control Letters, 1982, 1(5):288–294.MATHCrossRefGoogle Scholar
  3. [3]
    Song Qinbao, Shepperd M J, Carolyn M. Using Grey Relational Analysis to Predict Software Effort with Small Data Sets[C]// 11th IEEE International Software Metrics Symposium(METRICS 2005), Como, Italy, September 19–22, 2005.Google Scholar
  4. [4]
    Wang Yifan. On-Demand Forecasting of Stock Prices Using a Real-Time Predictor[J]. IEEE Transactions on Knowledge and Data Engineering, 2003, 15(4):1033–1037.CrossRefGoogle Scholar
  5. [5]
    Shen D H, Du J C. Grey Model for Asphalt Pavement Performance Prediction[C]//2004 IEEE Intelligent Transportation systems Conference. Washington D.C., October 3–6, 2004.Google Scholar
  6. [6]
    Huang S J, Huang C L. Control of an Inverted Pendulum Using Grey Prediction Model[J]. IEEE Transactions on Industry Applications, 2000, 36(2):452–458.CrossRefGoogle Scholar
  7. [7]
    Luo R C, Chen T M, Su K L. Target Tracking Using a Hierarchical Grey-Fuzzy Motion Decision-Making Method[J]. IEEE Transactions on Systems, Man and Cybernetics, Part A, 2001, 31(3):179–186.CrossRefGoogle Scholar
  8. [8]
    Su S L, Su Y C, Huang J F. Grey-Based Power Control for DS-CDMA Cellular Mobile Systems[J]. IEEE Transactions on Vehicular Technology, 2000, 49(6):2081–2088.CrossRefGoogle Scholar
  9. [9]
    Jou J M, Chen P Y, Sun J M. The Gray Prediction Search Algorithm for Block Motion Estimation[J]. IEEE Transactions on Circuits and Systems for Video Technology, 1999, 9(6):843–848.CrossRefGoogle Scholar
  10. [10]
    MacDonell S G, Shepperd M J. Using Prior-Phase Effort Records for Reestimation During Software Projects[C]//9th IEEE International Software Metrics Symposium (Metrics 2003). Sydney, Australia, September 3–5, 2003:73–86.Google Scholar
  11. [11]
    Kulkarni A, Greenspan J B, Kriegman D A, et al. A Generic Technique for Developing a Software Sizing and Effort Estimation Model[C]//Proc COMPSAC’88, Chicago, IL, October 3–6, 1988:151–161.Google Scholar
  12. [12]
    Deng Julong. Introduction to Grey System Theory[J]. The Journal of Grey System, 1989, 1(1):1–24.MATHMathSciNetGoogle Scholar
  13. [13]
    Liu Sifeng, Dang Yaoguo, Fang Zhigeng. Grey System Theory and Application[M]. Beijing: Science Press, 2004(Ch).Google Scholar

Copyright information

© Wuhan University 2007

Authors and Affiliations

  1. 1.Department of Computer ScienceXi’an Jiaotong UniversityXi’anChina

Personalised recommendations