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Utilization of statistical process control (SPC) in emergent software organizations: Pitfalls and suggestions


Common wisdom in the domain of software engineering tells us that companies should be mature enough to apply Statistical Process Control (SPC) techniques. Since reaching high maturity levels (in CMM or similar models such as ISO 15504) usually takes 5–10 years, should software companies wait years to utilize Statistical Process Control techniques? To answer this question, we performed a case study of the application of SPC techniques using existing measurement data in an emergent software organization. Specifically, defect density, rework percentage and inspection performance metrics are analyzed. This paper provides a practical insight on the usability of SPC for the selected metrics in the specific processes and describes our observations on the difficulties and the benefits of applying SPC to an emergent software organization.

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  1. Barnard, J. and Carleton, A.D. 1999. Analyzing Mature Software Inspection Process Using Statistical Process Control (SPC), The European SEPG Conference.

  2. Brooks, F.P. 1987. No Silver Bullet: Essence and Accidents of Software Engineering, IEEE Computer Magazine.

  3. Burr, A. and Owen, M. 1996. Statistical Methods for Software Quality. Thomson Publishing Company. ISBN 1-85032-171-X.

  4. Card, D. 1994. Statistical Process Control for Software?, IEEE Software pp. 95–97.

  5. Carleton, A.D. and Florac, A.W. 1999. Statistically Controlling the Software Process, The 99 SEI Software Engineering Symposium. Software Engineering Institute, Carnegie Mellon University.

  6. CMMI Product Team 2001. CMMISM for Systems Engineering, Software Engineering, and Integrated Product and Process Development (CMMI-SE/SW/IPPD, V1.1), Continuous Representation, Carnegie Mellon University.

  7. Crosby, P.B. 1980. Quality is Free: The Art of Making Quality Certain. Penguin Book USA Inc. ISBN: 0-451-62585-4.

  8. Florac, A.W. and Carleton, A.D. 1999. Measuring the Software Process: Statistical Process Control for Software Process Improvement. Pearson Education. ISBN 0-201-60444-2.

  9. Florac, A.W., Carleton, A.D., and Barnard, J.R. 2000. Statistical Process Control: Analyzing a Space Shuttle Onboard Software Process, IEEE Software, pp. 97–106.

  10. Florac, A.W., Park, E.R., and Carleton, A.D. 1997. Practical Software Measurement: Measuring for Process Management and Improvement (CMU/SEI-97-HB-003). Software Engineering Institute, Carnegie Mellon University.

  11. Heijstek, A. 1999. SPC in Ericsson, The European SEPG Conference.

  12. Hirsch, B. 1999. Can Statistical Process Control be Usefully Applied to Software? The European SEPG Conference.

  13. Humphrey, W. 1989. Managing the Software Process. Reading, Mass.: Addison-Wesley Publishing Company. ISBN 0-201-18095-2.

  14. IEEE Standard Classification for Software Anomalies, Std 1044-1993.

  15. IEEE Guide to Classification for Software Anomalies, Std 1044.1-1995.

  16. ISO/IEC 15504-4:1998(E), Information Technology—Software Process Assessment—Part 4: Guide to Performing Assessments.

  17. Jakolte, P. and Saxena, A. 2002. Optimum Control Limits for Employing Statistical Process Control in Software Process, IEEE Transactions on Software Engineering 28(12): 1126–1134.

  18. Kan, S.H. 1995. Metrics and Models in Software Quality Engineering. Addison-Wesley Publishing Company. ISBN 0-201-63339-6.

  19. Keller, T. 1999. Applying SPC Techniques to Software Development: A Management Perspective, The European SEPG Conference.

  20. Lantzy, M.A. 1992. Application of Statistical Process Control to Software Processes, WADAS ’92. Proceedings of the Ninth Washington Ada Symposium on Empowering Software Users and Developers. pp. 113–123.

  21. Meade, S. 1999. Lockheed Martin Mission Systems, The European SEPG Conference.

  22. Pajerski, R. and Sova, D. 1995. Software Measurement Guidebook, NASA GB-001-94. Software Engineering Program.

  23. Paulk, M.C. and Carleton, A.D. 1999. Can Statistical Process Control be Usefully Applied to Software? The 11th Software Engineering Process Group (SEPG) Conference.

  24. Paulk, M.C. and Chrissis, M.B. 2002. The 2001 High Maturity Workshop, (CMU/SEI 2001-SR-014), Carnegie Mellon University.

  25. Paulk, M.C., Weber, C.V., Garcia, S.M., Chrissis, M.B., and Bush, M. 1993. Key Practices of the Capability Maturity Model, Version 1.1. Software Engineering Institute, Carnegie Mellon University.

  26. Radice, R. 1998. Statistical Process Control for Software Projects, 10th Software Engineering Process Group Conference.

  27. Sargut, K.U. 2003. Application of Statistical Process Control to Software Development Processes via Control Charts, Middle East Technical University (Master’s Thesis).

  28. Shewhart, W.A. 1939. Statistical Method: From the Viewpoint of Quality Control, Lancaster Press Inc.

  29. Sutherland, J., Devor, R., and Chang, T. 1992. Statistical Quality Design and Control. Prentice Hall Publishing Company, ISBN: 002329180X.

  30. Weller, E. 2000. Practical Applications of Statistical Process Control, IEEE Software, pp. 48–55.

  31. Wigle, G.B. 1999. Quantitative Management in Software Engineering, The European SEPG Conference.

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Author information

Correspondence to K. U. Sargut.

Additional information

Umut Sargut He received his BS degree from Bilkent University Industrial Engineering department. After graduation, he started to work as a software engineer in Milsoft Software A.S. During his 2-year work experience, he participated in process improvement studies for measurement and problem resolution processes, and witnessed a successful CMM Level 3 assessment. He received his master’s degree in Information Systems from Middle East Technical University. Currently he is a PhD student in the University of Florida Computer and Information Sciences and Engineering Department.

Onur Demirörs He has Ph.D. and M.Sc. degrees in Computer Science from Southern Methodist University and B.Sc. degree in Computer Engineering from Middle East Technical University. He has been working in the domain of software engineering as an academician, researcher and consultant for the last 15 years. His work focuses on software process improvement, software project management, software engineering education, software engineering standards, and organizational change management. He managed a number of research and development projects on software process improvement, business process modeling and large scale software intensive system specification/acquisition. He has over 50 papers published in various books, journals and conferences and over 20 students have completed their graduate degrees under his supervision. He worked as a consultant for a number of software developing companies to improve their processes based on ISO 9001, ISO 15504 and CMM. He is currently working for Middle East Technical University as the head of the department of Information Systems – www.ii.metu.edu.tr.

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Sargut, K.U., Demirörs, O. Utilization of statistical process control (SPC) in emergent software organizations: Pitfalls and suggestions. Software Qual J 14, 135–157 (2006). https://doi.org/10.1007/s11219-006-7599-x

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  • Statistical process control
  • Control chart
  • Defect density
  • Rework percentage
  • Inspection performance