Skip to main content

Human-oriented improvement in the software process

  • Metrics session
  • Conference paper
  • First Online:
Software Process Technology (EWSPT 1996)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1149))

Included in the following conference series:

Abstract

By doing any task repeatedly, individuals can usually improve continuously due to the experience gained (called autonomous first-order learning). In addition, they can improve due to the injection of software development technology by the organization (called second-order learning). Organizations have studied such learning curves to make decisions regarding cost estimation and budgeting, production and labor scheduling, product pricing, etc. Such progress behavior was studied in a laboratory setting in an experiment involving a sample of 12 student software developers, who completed one small-sized project every week for ten weeks. A within-subject, repeated-measure, time-series quasi-experimental design was used as the research method. This also included the Goal/Question/Metric (GQM) paradigm with some additional validation techniques from Social Sciences/MIS/Software Engineering. Statistical tests showed that on average, progress takes place at a rate of about 20%, with technology injection (i.e., second-order learning) amounting to 13% improvement over autonomous learning alone. Such a distinction is useful for making personal decisions in software development and managerial decisions regarding training programs and making engineering technology changes. The study was replicated, twice, with samples of size 30 and 12. The average progress rate for the 54 subjects (in the three studies) was 18.51%.

This research is, in part, supported by NSERC, Canada.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Bibliography

  1. Call for Papers, 9th International Software Process Workshop, Airlie, Virginia, October 1994

    Google Scholar 

  2. Adler, P. and Clark, K., “Behind the Learning Curve: A Sketch of the Learning Process,” Management Science, vol. 37, no 3 (May 1991), pp 267–281

    Google Scholar 

  3. Albrecht, A., Gaffney J. “Software Function, Source Lines of Code, and Development Effort Prediction: A Software Science Validation,” IEEE Transactions on Software Engineering, vol. SE-9, no 6, Nov. 1983, pp 639–648

    Google Scholar 

  4. Argote, L., Beckman, S. and Epple, D. “The Persistence and Transfer of Learning in Industrial Settings,” Management Science, vol. 36, no 2, (Feb. 1992), pp 140–154

    Google Scholar 

  5. Arrow, K. “The Economic Implications of Learning by Doing,” Review of Economic Studies, vol. 29 (April 1962a), pp 166–170

    Google Scholar 

  6. Basili, V. “Quantitative Evaluation of Software Methodology,” Technical Report TR-1519, Dept of CS, University of Maryland, July 1985

    Google Scholar 

  7. Basili, V. and Weiss, D. “A Methodology for Collecting Valid Software Engineering Data,” IEEE Transactions on Software Engineering, vol. SE-10, no 6 (Nov. 1984) pp 728–738

    Google Scholar 

  8. Basili, V., Rombach H., “Goal Question Metric Paradigm,” Encyclopedia of Software Engineering, vol. 2, 1994, John Wiley & Sons, Inc.

    Google Scholar 

  9. Basili, V., Selby R. “Comparing the Effectiveness of Software Testing Strategies,” IEEE Transactions on Software Engineering, vol. SE-13, no 12, Dec. 1987, pp 1278–1296

    Google Scholar 

  10. Boehm, B. “Software Engineering Economics,” 1981, Prentice-Hall, Englewood Cliffs, NJ

    Google Scholar 

  11. Curtis, B., et al. “Productivity Factors and Programming Environments,” Proceedings of the Seventh International Conference on Software Engineering, Washington DC, IEEE Computer Society, pp. 143–152

    Google Scholar 

  12. Dutton, J., Thomas, A. and Butler, J. “The History of Progress Functions as a Managerial Technology,” Business History Review, vol. 58 (Summer 1984), pp 204–233

    Google Scholar 

  13. Emam, K. E., Moukheiber, N. and Madhavji, N. “The Empirical Evaluation of the GQM,” Proceedings CASCON 1993, vol. 2, pp 265–289

    Google Scholar 

  14. Emam, K. E., Shostak B., Madhavji N. H., “Implementing the Personal Software Process in an Industrial Setting,” Proc. 4th Int. Conf. on Software Process, Brighton, U.K., Dec 1996 (To appear)

    Google Scholar 

  15. Fagan, M. “Advances in Software Inspections,” IEEE Transactions on Software Engineering, vol. SE-12, no 7, Jul. 1986, pp 744–751

    Google Scholar 

  16. Hirsch, W. “Manufacturing Progress Functions,” The Review of Economics and Statistics, vol. 34 (May 1952), pp 143–155

    Google Scholar 

  17. Humphrey, W. “A Discipline for Software Engineering,” Addison Wesley, 1995

    Google Scholar 

  18. Kemerer, C. F. “How the Learning Curve Affects Case Tool Adoption,” IEEE Software, May 1992, pp 23–28

    Google Scholar 

  19. Kemerer, C., Porter B. “Improving the Reliability of Function Point Measurement An Empirical Study,” IEEE Transactions on Software Engineering, Vol. 18, No 11, Nov.92, pp 1011–1024

    Google Scholar 

  20. Kerlinger, F. “Foundations of Behavioral Research,” 3rd ed., 1986, Holt, Rinehart and Winston, New York, NY

    Google Scholar 

  21. Kidder, L. “Research Methods in Social Relations,” 5th ed., 1986, Hold, Rinehart and Winston, NY.

    Google Scholar 

  22. Kleinbaum, D. “Applied Regression Analysis and other Multivariable Methods,” 2nd ed., 1988, PWS-Kent Pub. Co., Boston, MA

    Google Scholar 

  23. Levy, F. K. “Adaptation in the Production Process,” Management Science, vol. 11, no 6, (April 1965), pp B136–B154

    Google Scholar 

  24. Miles, R. E., Snow, C. C., “Organizational strategy, structure and process,” McGraw-Hill, NY, 1978

    Google Scholar 

  25. Rapping, L. “Learning and World War II Production Functions,” Review of Economics and Statistics, vol. 47, 1965, pp 81–86

    Google Scholar 

  26. Ripley, D., Druseikis F. “A Statistical Analysis of Syntax Errors,” Computer Languages, Vol. 3, 1978, pp 227–240

    Google Scholar 

  27. Rosenthal, R. “Essentials of Behavioral Research: Methods and Data Analysis,” 1984, McGraw-Hill, New York, NY

    Google Scholar 

  28. Russell, G. “Experience with Inspection in Ultra-Scale Developments,” IEEE Software, Jan 91, pp 25–31

    Google Scholar 

  29. Shepperd, M. “An Evaluation of Software Product Metrics,” Information and Software Technology, Vol. 30, No 3, April 1988, pp 177–188

    Google Scholar 

  30. Sherdil, K., “Personal Progress Functions in the Software Process,” Masters Thesis, School of Comupter Science, McGill University, Montreal, QC, Feb 1995

    Google Scholar 

  31. Sherdil, K., Madhavji N. “Personal Progress Functions in the Software Process,” Proceedings of 9th International Software Process Workshop, Airlie, Virginia, IEEE Computer Society, Oct 1994, pp 117–121

    Google Scholar 

  32. Straub, D. “Validating Instruments in MIS Research,” MIS Quarterly, June 1989

    Google Scholar 

  33. Yelle, L. “The Learning Curve: Historical Review and Comprehensive Survey,” Decision Sciences, vol. 10 (Feb. 1979), pp 302–328

    Google Scholar 

  34. Victor Basili, Gianluigi Caldiera, and Hans-Dieter Rombach. Goal Question Metric Paradigm. In [Mar94], 1994.

    Google Scholar 

  35. Norman Fenton, Shari Lawrence Pfleeger, and Robert L. Glass. Science and Substance: A Challenge to Software Engineers. IEEE Software, 11(7):86–95, July 1994.

    Google Scholar 

  36. Robert B. Grady and Deborah L. Caswell. Software Metrics — Establishing a Company-Wide Program (for HP). PTR Prentice-Hall Inc., 1987.

    Google Scholar 

  37. John J. Marciniak, editor. Encyclopedia of Software Engineering. John Wiley and Sons, 1994.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Carlo Montangero

Rights and permissions

Reprints and permissions

Copyright information

© 1996 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Sherdil, K., Madhavji, N.H. (1996). Human-oriented improvement in the software process. In: Montangero, C. (eds) Software Process Technology. EWSPT 1996. Lecture Notes in Computer Science, vol 1149. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0017741

Download citation

  • DOI: https://doi.org/10.1007/BFb0017741

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61771-6

  • Online ISBN: 978-3-540-70676-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics