Advertisement

A Software Implementation Progress Model

  • Dwayne Towell
  • Jason Denton
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3922)

Abstract

Software project managers use a variety of informal methods to track the progress of development and refine project schedules. Previous formal techniques have generally assumed a constant implementation pace. This is at odds with the experience and intuition of many project managers. We present a simple model for charting the pace of software development and helping managers understand the changing implementation pace of a project. The model was validated against data collected from the implementation of several large projects.

Keywords

Software Engineer Polynomial Model Source Line Software Metrics Progress Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Boehm, B.W.: Software Engineering Economics. Prentice-Hall, Englewood Cliffs (1981)MATHGoogle Scholar
  2. 2.
    McConnell, S.: Software Project Survival Guide. Microsoft Press, Redmond (1998)Google Scholar
  3. 3.
    Fenton, N.E.: Software Metrics: A Rigorous Approach. Chapman and Hall, London (1991)MATHGoogle Scholar
  4. 4.
    Kafura, D., Canning, J.: A validation of software metrics using many metrics and two resources. In: Proceedings of the 8th International Conference on Software Engineering, pp. 378–385 (1985)Google Scholar
  5. 5.
    Fenton, N.E., Neil, M.: Software metrics: roadmap. In: Proceedings of the conference on The future of Software Engineering, pp. 357–370. ACM Press, New York (2000)Google Scholar
  6. 6.
    Albrecht, A.J., John, E., Gaffney, J.: Software function, source lines of code, and development effort prediction: A software science validation. IEEE Transactions on Software Engineering 9(6), 639–648 (1983)CrossRefGoogle Scholar
  7. 7.
    Humphrey, W.S.: A Discipline for Software Engineering. Addison-Wesley, Reading (1994)Google Scholar
  8. 8.
    Schneidewind, N.F.: Measuring and evaluating maintenance process using reliability, risk, and test metrics. IEEE Transactions on Software Engineering 25(6), 761–781 (1999)CrossRefGoogle Scholar
  9. 9.
    Beck, K.: Extreme Programming Explained: Embrace Change. Addison-Wesley, Reading (1999)Google Scholar
  10. 10.
    Towell, D.: An implementation progress model. Master’s thesis, Texas Tech University (2004)Google Scholar
  11. 11.
    De Marco, T.: Controlling Software Projects - Management, Measurement and Estimation. Yourdon Press, Inglewood Cliffs (1982)Google Scholar
  12. 12.
    Lind, R.K., Vairavan, K.: An experiemental investigation of software metrics and their relationship to software development effort. IEEE Transactions on Software Engineering 15(5), 649–653 (1989)CrossRefGoogle Scholar
  13. 13.
    Jorgensen, M.: Experience with the accuracy of software maintenance task effort prediction models. IEEE Transactions on Software Engineering 21(8), 674–681 (1995)CrossRefGoogle Scholar
  14. 14.
    El-Eman, K.: A methodology for validating software product metrics. Technical Report NRC/ERB-1076 44142, National Research Council Canada, Institute for Information Technology (2000)Google Scholar
  15. 15.
    Sackman, H., Erikson, W.J., Grant, E.E.: Exploratory experimentation studies comparing online and offline programming performance. Communications of the ACM 1(1), 3–11 (1968)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Dwayne Towell
    • 1
  • Jason Denton
    • 2
  1. 1.Abilene Christian UniversityAbileneUSA
  2. 2.Texas Tech UniversityAbileneUSA

Personalised recommendations