Measurement and Effort Prediction for Web Applications

  • Emilia Mendes
  • Steve Counsell
  • Nile Mosley
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2016)


Accurate estimates of development effort play an important role in the successful management of larger Web development projects. However, estimating the effort required in developing Web applications can be a difficult task. By applying measurement principles to measure the quality of applications and their development processes, feedback can be obtained to help control, improve and predict products and processes. Although to date most work in software effort estimation has focused on algorithmic cost models, in recent years research in the field of effort estimation has started to move towards non-algorithmic models, where “estimation by analogy” is one of the available techniques. The first part of this paper describes a case study evaluation (CSE) where proposed metrics and the effort involved in authoring Web applications were measured. The second half presents the use of analogy and two algorithmic models - linear regression and stepwise multiple regression - to estimate the authoring effort of Web applications, based on the datasets obtained from the CSE. Results suggest that estimation by analogy is a superior technique and that, with the aid of an automated environment, it is a practical technique to apply to Web authoring prediction.


Stepwise Multiple Regression Effort Estimation Effort Prediction Software Effort Estimation Case Study Evaluation 
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.


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  1. 1.
    Brown, P.J.: Creating Educational Hyperdocuments: Can It Be Economic?. IETI-Innovations in Education and Training Technology, Vol. 32. No. 3. (1995) 202–208.Google Scholar
  2. 2.
    Lowe, D.,and Hall, W.: Hypertext and the Web-An Engineering Approach. John Wiley & Sons Ltd. (eds.) (1998).Google Scholar
  3. 3.
    Shepperd, M.J., Schofield, C., and Kitchenham, B.: Effort Estimation Using Analogy. Proc. ICSE-18. IEEE Computer Society Press Berlin. (1996).Google Scholar
  4. 4.
    Conklin, J.: Hypertext: An Introduction and Survey. IEEE COMPUTER. Sept.. (1987) 17–37.Google Scholar
  5. 5.
    Botafogo, R., Rivlin, A. E., and Shneiderman, B.: Structural Analysis of Hypertexts: Identifying Hierarchies and Useful Metrics. ACM TOIS. Vol. 10. No. 2. (1992) 143–179.Google Scholar
  6. 6.
    Whalley, P.: Models of Hypertext Structure and Learning. In: D. H. Jonassen and H. Mandl (eds.): Designing Hypermedia for Learning, Berlin, Heidelberg: Springer-Verlag (1990) 61–67.Google Scholar
  7. 7.
    Kitchenham, B., Pfleeger, S. L., and Fenton, N.: Towards a Framework for Software Measurement Validation. IEEE Transactions on Software Engineering, Vol. 21, No. 12, (1995) 929–944.CrossRefGoogle Scholar
  8. 8.
    Mendes, E.: Investigating Metrics for a Development Effort Prediction Model of Web Applications. Proc. ASWEC 2000, IEEE Computer Society Press, Canberra, ACT, Australia, (2000).Google Scholar
  9. 9.
    Spiro, R. J. P., Feltovich, J., Jacobson, M. J., and R. Coulson, L.: Cognitive Flexibility, Constructivism, and Hypertext: Random Access Instruction for Advanced Knowledge Acquisition in Ill-Structured Domains. In: L. Steffe & J. Gale (eds.): Constructivism, Hillsdale, N.J.:Erlbaum (1995).Google Scholar
  10. 10.
    Kitchenham, B., Pickard, L., and Pfleeger, S. L.: Case Studies for Method and Tool Evaluation, IEEE Software, July, (1995) 52–62.Google Scholar
  11. 11.
    Balasubramanian, P., Isakowitz, T., and Stohr, E. A.: RMD: A Methodology for the Design of Hypermedia Applications. Proc. Workshop on Hypermedia Design and Development, Edinburgh, September, (1994) 33–38.Google Scholar
  12. 12.
    Ginige, A., Lowe, D. B. and Robertson, J.: Hypermedia Authoring. IEEE MultiMedia, Winter (1995) 24–35.Google Scholar
  13. 13.
    Schwabe, D., and Rossi, G.: Building Hypermedia Applications as Navigational Views of Information Models. Proc.28th Annual Hawaii International Conference on System Sciences, (1995) 231–240.Google Scholar
  14. 14.
    McDonell, S. G., and Fletcher, T.: Metric Selection for Effort Assessment in Multimedia Systems Development. Proc. Metrics’98, (1998).Google Scholar
  15. 15.
    Thackaberry, W., and Rada, R.: Estimation Metrics for Courseware Maintenance Effort. Journal of Universal Computer Science, Vol. 4, No. 3, (1998) 308–325.Google Scholar
  16. 16.
    Mendes, M. E. X.: Developing Metrics for Improving Hypermedia Authoring. PhD Thesis, Department of Electronics and Computer Science, Southampton, UK, March. (1999).Google Scholar
  17. 17.
    Boehm-Davis, D.A., and Ross, L. S.: Program design methodologies and the software development process. International Journal of Man-Machine Studies, Academic Press Limited, Vol. 36, (1992) 1–19.CrossRefGoogle Scholar
  18. 18.
    Myrtveit, I., and E. Stensrud: A Controlled Experiment to Assess the Benefits of Estimating with Analogy and Regression Models. IEEE Transactions on Software Engineering, Vol. 25, No. 4, Jul./Aug. (1999) 510–525.CrossRefGoogle Scholar
  19. 19.
    Mason, R. L., Gunst, R. F., and Hess, J. L.: Statistical Design and Analysis of Experiments with applications to Engineering and Science, Wiley:New York, Chichester, Brisbane, Toronto, Singapore, (1989) 435–440.Google Scholar
  20. 20.
    Shepperd, M. J., and Schofield, C.: Estimating Software Project Effort Using Analogies. IEEE Transactions on Software Engineering, Vol. 23, No. 11, (1997) 736–743.CrossRefGoogle Scholar
  21. 21.
    Fenton, N. E, and Pfleeger, S. L.: Software Metrics, A Rigorous & Practical Approach, 2nd edition, PWS Publishing Company and International Thomson Computer Press, (1997).Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Emilia Mendes
    • 1
  • Steve Counsell
    • 2
  • Nile Mosley
    • 3
  1. 1.Department of Computer Sciencethe University of AucklandAucklandNew Zealand
  2. 2.Computer Science DepartmentBirkbeck College
  3. 3.MXM TechnologyNew Zealand

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