A Software Implementation Progress Model

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


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.


Software Engineer Polynomial Model Source Line Software Metrics Progress Model 
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  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

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