A model for analyzing estimation, productivity, and quality performance in the personal software process

ABSTRACT

High-maturity software development processes, making intensive use of metrics and quantitative methods, such as the Team Software Process (TSP) and the accompanying Personal Software Process (PSP), can generate a significant amount of data that can be periodically analyzed to identify performance problems, determine their root causes and devise improvement actions. However, there is a lack of tool support for automating the data analysis and the recommendation of improvement actions, and hence diminish the manual effort and expert knowledge required. So, we propose in this paper a comprehensive performance model, addressing time estimation accuracy, quality and productivity, to enable the automated (tool based) analysis of performance data produced in the context of the PSP, namely, identify performance problems and their root causes, and subsequently recommend improvement actions. Performance ranges and dependencies in the model were calibrated and validated, respectively, based on a large PSP data set referring to more than 30,000 finished projects.

References

1. Bohem, B. 2011. Some Future Software Engineering Opportunities and Challenges. In The Future of Software Engineering, Springer-Verlag, 1-32.
2. Humphrey, W. 2005. PSP sm : A Self-Improvement Process for Software Engineers. Addison-Wesley Professional.
3. Davis, N. and Mullaney, J. 2003. The Team Software Process (TSP) in Practice: A Summary of Recent Results. CMU/SEI- 2003-TR-014.
4. Rombach, D., Münch, J., Ocampo, A., Humphrey, W., and Burton, B. 2008. Teaching disciplined software development. Journal of Systems and Software 81(5): 2008, 747-763.
5. Pomeroy-Huff, M., Cannon, R., Chick, T., Mullaney, J., and Nichols, W. 2009. The Personal Software Process SM (PSP SM ) Body of Knowledge (Version 2.0). CMU/SEI-2009-SR-018.
6. Burton, D. and Humphrey, W. 2006. Mining PSP Data. In TSP Symposium 2006 Proceedings.
7. The Software Process Dashboard Initiative home page. http://www.processdash.com/.
8. Philip, J., Kou, H., Agustin, J., Christopher, C., Moore, C., Miglani, J., Zhen, S., Doane, W. 2003. Beyond the Personal Software Process: Metrics Collection and Analysis for the Differently Disciplined. In ICSE 2003. Portland, Oregon.
9. Shin, H., Choi, H., and Baik, J. 2007. Jasmine: A PSP Supporting Tool. In Proc. of the Int. Conf. on Software Process (ICSP 2007), LNCS 4470, Springer-Verlag, 73-83.
10. Nasir, M. and Yusof, A. 2005. Automating a Modified Personal Software Process. Malaysian Journal of Computer Science, vol. 18, 11–27.
11. Kemerer, C., and Paulk, M. 2009. The Impact of Design and Code Reviews on Software Quality: An Empirical Study Based on PSP Data. IEEE Transactions on Software Engineering, vol. 35, Issue 4, 534-550.
12. Shen, W., Hsueh, N., Lee, W. 2011. Assessing PSP effect in training disciplined software development: A Plan–Track– Review model. Inform. and Soft.Technology 53, 137–148.
13. Duarte, C., Faria, J., and Raza, M. 2012. PSP PAIR: Automated Personal Software Process Performance Analysis and Improvement Recommendation. In Proc. of the 8th Int. Conf. on the Quality of Information and Communications Technology, IEEE CPS, Lisbon, Portugal.
14. Duarte, C., Faria, F., Raza, M., Henriques, P. 2012. Model and Tool for Analyzing Time Estimation Performance in PSP. In TSP Symposium 2012, CMU/SEI-2012-SR-015, 21- 40.
15. Raza, M., Faria, J., Henriques, P., and Nichols, W. 2013. Factors Affecting Productivity Performance in PSP Training. In TSP Symposium 2013., CMU/SEI-2013-SR-022, 35-45.
16. Raza, M., Faria, J. 2014. Factors Affecting Personal Software Development Productivity: A Case Study with PSP Data. In IASTED SE 2014.
17. Jones, C. 2000. Software Assessments, Benchmarks, and Best Practices. Addison Wesley.
18. Humphrey, W. 2009. The Software Quality Profile. White Paper, SEI.
19. Chillargee, R., Bhandari, I., et. al. 1992. Orthogonal Defect Classification - A Concept for In-Process Measurements. IEEE Trans. on Software Eng., Vol. 18, Issue 11, 943-956.
20. Card, D. 2005. Defect Analysis: Basic Techniques for Management and Learning. Advances in Computers, vol.64, 259-295. Elsevier.
21. Ferreira, A., Machado, R., Costa, L., Silva, J., Batista, R., and Paulk, M. 2010. An Approach to Improving Software Inspections Performance. In Proc. of the 2010 IEEE Int. Conf. on Soft.Maintenance, 1-8, ISBN 978-1-4244-8640-4.
22. Tamura, S. 2009. Integrating CMMI and TSP/PSP: Using TSP Data to Create Process Performance Models. CMU/SEI- 2009-TN-033.
23. Wagner, S. and Ruhe, M. 2008. A Systematic Review of Productivity Factors in Software Development. In Proc. of 2nd Int. Workshop on Software Productivity Analysis and Cost Estimation (SPACE 2008).
24. Maxwell, K. and Forselius, P. 2000. Benchmarking Software Development Productivity. IEEE Software, 17(2), 80-88.
25. Goparaju, P., Farooq, A., Patnaikc, S. 2012. Measuring Productivity of Software Development Teams. Serbian Journal of Management 7 (1) (2012), 65-75.
26. Card, D. 2006. The Challenge of Productivity Measurement. In Proc. of the Pacific Northwest Software Quality Conference, Portland, OR.
27. Jones, C. 2010. Software Engineering Best Practices: Lessons from Successful Projects in the Top Companies. McGraw-Hill.
28. Scacchi, W. 1995. Understanding Software Productivity. Software Engineering and Knowledge Engineering: Trends for the Next Decade. World Scientific Press.
29. Comstock, C., Jiang, Z., and Naudé, P. 2007. Strategic Software Development: Productivity Comparisons of General Development Programs. Int. Journal of Computer and Information Engineering 1:8 2007, 486-491.
30. Banker, R. and Kauffman, R. 1991. Reuse and Productivity in Integrated Computer-Aided Software Engineering: An Empirical Study. MIS Quarterly, Sept 1991, 14(3):374-401
31. Alves, T. 2012. Benchmark-based Software Product Quality Evaluation. Doctoral Thesis. University of Minho.
32. Navidi, W. 2011. Statistics for Engineers and Scientists, Third Edition, McGraw-Hill.

Index Terms

• Social and professional topics

  • Professional topics

    • Management of computing and information systems

      • Project and people management

• Software and its engineering

  • Software creation and management

    • Software development process management

  • Software notations and tools

    • Software configuration management and version control systems