A Methodology for the Development of Process Performance Models for Quantitative Management of Software Projects
Abstract
Statistical process control has been used in order to control the performance of software processes. However, this technique is limited to control the value of a metric in a current project, compared to the same metric considering the process performance. In this paper we present a quantitative project management methodology combining statistical process control and statistical performance models to allow predicting behaviors for different scenarios to support managerial decisions. The methodology was developed during the application of those techniques in a software organization to control and relate the Quality Assurance and Verification processes.
Keywords:
Quantitative Management, Performance Models, Development Methodology
References
Crissis, M.B., Konrad, M., Shrum, S. (2006), CMMI - Guidelines for Process Integration and Product Improvement (2nd Edition), SEI Series in Software Engineering, Addison-Wesly Professional.
D'Agostino, Stephens (1986), Goodness-Of-Fit Techniques, Marcel-Dekker, New York, Table 4.7, p.123. All of Chapter 4, pp.97-193, deals with goodness-of-fit tests based on empirical distribution function (EDF) statistics
Fairley, R.E. (1999), “Managing by the Numbers: A tutorial on quantitative measurement and control of software projects”, in: International Conference on Software Engineering, ICSE'99, Los Angeles, CA.
Fenton, N.E. (1999), “A Critique of Software Defect Prediction Models”, IEEE Transactions on Software Engineering, vol 25, no 5.
Florac, W.A., Carleton, A.D. (1999), Measuring the Software Process — Statistical Process Control for Software Process Improvement, Addison-Wesley.
Hong, G.Y., Xie, M., Shanmugan, P. (1999), A Statistical Method For Controlling Software Defect Detection Process, J. on Comp. and Industrial Engineering, vol. 37.
Maxwell, K.D. (2002), Applied Statistics for Software Managers, Software Quality Institute Series, Prentice-Hall.
MPS.BR — Melhoria de Processo do Software Brasileiro, Guia Geral v1.1, (2006), Maio, http://www.softex.br/mpsbr/_guias/MPS.BR Guia Geral V1.1.pdf.
Munson, J.C., Khoshgoftaar, T.M. (1990) “Regression Modelling of Software Quality: An Empirical Investigation,” Information and Software Technology, vol. 32, no. 2, pp. 106-114, 1990.
Shewhart, W.A. (1931), Economic Control of Quality of Manufactured Products, Van Nostrand, New York.
Solingen, R., Berghout, E. (1999), The Goal/Question/Metric Method — A Practical Guide for Quality Improvement of Software Development, McGrawHIill.
Wang, Q., Jiang, N., Gou, L., Liu, X., Li, M., Wang, Y. (2006), BSR: A Statistic-based Approach for Establishing and Refining Software Process Performance Baseline, in: Int. Conf. on Soft. Eng., ICSE'06, ACM Press, New York, NY, USA, pp. 585-594.
Wheeler, Donald J. (1999). Understanding Variation: The Key to Managing Chaos, 2nd Edition. SPC Press.
D'Agostino, Stephens (1986), Goodness-Of-Fit Techniques, Marcel-Dekker, New York, Table 4.7, p.123. All of Chapter 4, pp.97-193, deals with goodness-of-fit tests based on empirical distribution function (EDF) statistics
Fairley, R.E. (1999), “Managing by the Numbers: A tutorial on quantitative measurement and control of software projects”, in: International Conference on Software Engineering, ICSE'99, Los Angeles, CA.
Fenton, N.E. (1999), “A Critique of Software Defect Prediction Models”, IEEE Transactions on Software Engineering, vol 25, no 5.
Florac, W.A., Carleton, A.D. (1999), Measuring the Software Process — Statistical Process Control for Software Process Improvement, Addison-Wesley.
Hong, G.Y., Xie, M., Shanmugan, P. (1999), A Statistical Method For Controlling Software Defect Detection Process, J. on Comp. and Industrial Engineering, vol. 37.
Maxwell, K.D. (2002), Applied Statistics for Software Managers, Software Quality Institute Series, Prentice-Hall.
MPS.BR — Melhoria de Processo do Software Brasileiro, Guia Geral v1.1, (2006), Maio, http://www.softex.br/mpsbr/_guias/MPS.BR Guia Geral V1.1.pdf.
Munson, J.C., Khoshgoftaar, T.M. (1990) “Regression Modelling of Software Quality: An Empirical Investigation,” Information and Software Technology, vol. 32, no. 2, pp. 106-114, 1990.
Shewhart, W.A. (1931), Economic Control of Quality of Manufactured Products, Van Nostrand, New York.
Solingen, R., Berghout, E. (1999), The Goal/Question/Metric Method — A Practical Guide for Quality Improvement of Software Development, McGrawHIill.
Wang, Q., Jiang, N., Gou, L., Liu, X., Li, M., Wang, Y. (2006), BSR: A Statistic-based Approach for Establishing and Refining Software Process Performance Baseline, in: Int. Conf. on Soft. Eng., ICSE'06, ACM Press, New York, NY, USA, pp. 585-594.
Wheeler, Donald J. (1999). Understanding Variation: The Key to Managing Chaos, 2nd Edition. SPC Press.
Published
2007-06-01
How to Cite
MONTONI, Mariano; KALINOWSKI, Marcos; LUPO, Peter; ABRANTES, José Fortuna; FERREIRA, Analia Irigoyen Ferreiro; ROCHA, Ana Regina.
A Methodology for the Development of Process Performance Models for Quantitative Management of Software Projects. In: BRAZILIAN SOFTWARE QUALITY SYMPOSIUM (SBQS), 6. , 2007, Porto de Galinhas.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2007
.
p. 325-339.
DOI: https://doi.org/10.5753/sbqs.2007.15585.
