How to cite this paper
John, B., Kadadevaramath, R & Edinbarough, I. (2016). Application of multistage process control methodology for software quality management.Journal of Project Management, 1(2), 55-66.
Refrences
Adam Jr, E. E., Flores, B. E., & MacIas, A. (2001). Quality improvement practices and the effect on manufacturing firm performance: evidence from Mexico and the USA. International Journal of Production Research, 39(1), 43-63.
Antony, J., & Fergusson, C. (2004). Six Sigma in the software industry: results from a pilot study. Managerial Auditing Journal, 19(8), 1025-1032.
Asher, M., & Kanji, G. K. (1996). 100 Methods for Total Quality Management. Sage Publications.
Bag, M., Gauri, S., & Chakraborty, S. (2012). Feature-based decision rules for control charts pattern recognition: A comparison between CART and QUEST algorithm. International Journal of Indus-trial Engineering Computations, 3(2), 199-210.
Black, G., Smith, J., & Wells, S. (2011). The impact of Weibull data and autocorrelation on the per-formance of the Shewhart and exponentially weighted moving average control charts. International Journal of Industrial Engineering Computations, 2(3), 575-582.
Ceylan, E., Kutlubay, F. O., & Bener, A. B. (2006, August). Software defect identification using ma-chine learning techniques. In Software Engineering and Advanced Applications, 2006. SEAA'06. 32nd EUROMICRO Conference on (pp. 240-247). IEEE.
Crawley, M. J. (2012). The R book. John Wiley & Sons.
Ding, Y., Shi, J., & Ceglarek, D. (2002, January). Diagnosability analysis of multi-station manufac-turing processes. In ASME 2002 International Mechanical Engineering Congress and Exposition (pp. 475-484). American Society of Mechanical Engineers.
Djurdjanovic, D. R. A. G. A. N., & Ni, J. (2001). Linear state space modeling of dimensional machin-ing errors. Transactions-North American Manufacturing Research Institution of SME, 541-548.
Fenton, N., & Bieman, J. (2014). Software metrics: a rigorous and practical approach. CRC Press.
Friedman, J., Hastie, T., & Tibshirani, R. (2001). The elements of statistical learning (Vol. 1). Spring-er, Berlin: Springer series in statistics.
Hao, Y., & Zhang, Y. F. (2011, May). Statistical prediction modeling for software development pro-cess performance. In Communication Software and Networks (ICCSN), 2011 IEEE 3rd Interna-tional Conference on (pp. 703-706). IEEE.
Harter, D. E., Krishnan, M. S., & Slaughter, S. A. (2000). Effects of process maturity on quality, cy-cle time, and effort in software product development. Management Science, 46(4), 451-466.
Hawkins, D. M. (1993). Regression adjustment for variables in multivariate quality control. Journal of Quality Technology, 25(3), 170-182.
Herbsleb, J., Zubrow, D., Goldenson, D., Hayes, W., & Paulk, M. (1997). Software quality and the capability maturity model. Communications of the ACM, 40(6), 30-40.
Iso, I., & Std, I. E. C. (2001). 9126 Software product evaluation–quality characteristics and guide-lines for their use. ISO/IEC Standard, 9126.
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning (Vol. 6). New York: springer.
Jayathavaj, V., & Pongpullponsak, A. (2014). A simulation study on the performance of the sign test, Mann-Whitney test, Hodges-Lehmann estimator and control charts for Normal and Weibull data. International Journal of Industrial Engineering Computations, 5(4), 561-574.
Jin, J., & Shi, J. (1999). State space modeling of sheet metal assembly for dimensional control. Jour-nal of Manufacturing Science and Engineering, 121(4): 756-762.
John, B., & Kadadevarmath, R. (2015). A methodology for quantitatively managing the bug fixing process using Mahalanobis Taguchi system. Management Science Letters, 5(12), 1081-1090.
Montgomery, D. C. (2007). Introduction to statistical quality control. John Wiley & Sons.
Myatt, G. J. (2007). Making sense of data: a practical guide to exploratory data analysis and data min-ing. John Wiley & Sons.
Noghondarian, K., & Ghobadi, S. (2012). Developing a univariate approach to phase-I monitoring of fuzzy quality profiles. International Journal of Industrial Engineering Computations, 3(5), 829-842.
Neil, M. (1992). Multivariate assessment of software products. Softw. Test., Verif. Reliab., 1(4), 17-37.
Paulk, M. C. (1993). Comparing ISO 9001 and the capability maturity model for software. Software Quality Journal, 2(4), 245-256.
Pressman, R. S. (2005). Software engineering: a practitioner's approach. Palgrave Macmillan.
Samson, D., & Terziovski, M. (1999). The relationship between total quality management practices and operational performance. Journal of operations management, 17(4), 393-409.
Shu, L., & Tsung, F. (2003). On multistage statistical process control. Journal of the Chinese Institute of Industrial Engineers, 20(1), 1-8.
Shu, L., Apley, D. W., & Tsung, F. (2002). Autocorrelated process monitoring using triggered cuscore charts. Quality and Reliability Engineering International, 18(5), 411-421.
Shu, L., Tsung, F., & Kapur, K. C. (2004). Design of multiple cause-selecting charts for multistage processes with model uncertainty. Quality Engineering, 16(3), 437-450.
Shu, L., Tsung, F., & Tsui, K. L. (2005). Effects of estimation errors on cause-selecting charts. IIE transactions, 37(6), 559-567.
Song, Q., Shepperd, M., Cartwright, M., & Mair, C. (2006). Software defect association mining and defect correction effort prediction. IEEE Transactions on Software Engineering, 32(2), 69-82.
Tamura, S. (2009). CMMI and TSP/PSP: Using TSP Data to Create Process Performance Models.
Team, R. C. (2014). R: A language and environment for statistical computing. R Foundation for Sta-tistical Computing, Vienna, Austria. 2013.
Tsung, F., Li, Y., & Jin, M. (2008). Statistical process control for multistage manufacturing and ser-vice operations: a review and some extensions. International Journal of Services Operations and In-formatics, 3(2), 191-204.
Turhan, B., & Bener, A. (2007, October). A multivariate analysis of static code attributes for defect prediction. In Quality Software, 2007. QSIC'07. Seventh International Conference on (pp. 231-237). IEEE.
Zantek, P. F., Wright, G. P., & Plante, R. D. (2006). A self-starting procedure for monitoring process quality in multistage manufacturing systems. IIE Transactions, 38(4), 293-308.
Antony, J., & Fergusson, C. (2004). Six Sigma in the software industry: results from a pilot study. Managerial Auditing Journal, 19(8), 1025-1032.
Asher, M., & Kanji, G. K. (1996). 100 Methods for Total Quality Management. Sage Publications.
Bag, M., Gauri, S., & Chakraborty, S. (2012). Feature-based decision rules for control charts pattern recognition: A comparison between CART and QUEST algorithm. International Journal of Indus-trial Engineering Computations, 3(2), 199-210.
Black, G., Smith, J., & Wells, S. (2011). The impact of Weibull data and autocorrelation on the per-formance of the Shewhart and exponentially weighted moving average control charts. International Journal of Industrial Engineering Computations, 2(3), 575-582.
Ceylan, E., Kutlubay, F. O., & Bener, A. B. (2006, August). Software defect identification using ma-chine learning techniques. In Software Engineering and Advanced Applications, 2006. SEAA'06. 32nd EUROMICRO Conference on (pp. 240-247). IEEE.
Crawley, M. J. (2012). The R book. John Wiley & Sons.
Ding, Y., Shi, J., & Ceglarek, D. (2002, January). Diagnosability analysis of multi-station manufac-turing processes. In ASME 2002 International Mechanical Engineering Congress and Exposition (pp. 475-484). American Society of Mechanical Engineers.
Djurdjanovic, D. R. A. G. A. N., & Ni, J. (2001). Linear state space modeling of dimensional machin-ing errors. Transactions-North American Manufacturing Research Institution of SME, 541-548.
Fenton, N., & Bieman, J. (2014). Software metrics: a rigorous and practical approach. CRC Press.
Friedman, J., Hastie, T., & Tibshirani, R. (2001). The elements of statistical learning (Vol. 1). Spring-er, Berlin: Springer series in statistics.
Hao, Y., & Zhang, Y. F. (2011, May). Statistical prediction modeling for software development pro-cess performance. In Communication Software and Networks (ICCSN), 2011 IEEE 3rd Interna-tional Conference on (pp. 703-706). IEEE.
Harter, D. E., Krishnan, M. S., & Slaughter, S. A. (2000). Effects of process maturity on quality, cy-cle time, and effort in software product development. Management Science, 46(4), 451-466.
Hawkins, D. M. (1993). Regression adjustment for variables in multivariate quality control. Journal of Quality Technology, 25(3), 170-182.
Herbsleb, J., Zubrow, D., Goldenson, D., Hayes, W., & Paulk, M. (1997). Software quality and the capability maturity model. Communications of the ACM, 40(6), 30-40.
Iso, I., & Std, I. E. C. (2001). 9126 Software product evaluation–quality characteristics and guide-lines for their use. ISO/IEC Standard, 9126.
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning (Vol. 6). New York: springer.
Jayathavaj, V., & Pongpullponsak, A. (2014). A simulation study on the performance of the sign test, Mann-Whitney test, Hodges-Lehmann estimator and control charts for Normal and Weibull data. International Journal of Industrial Engineering Computations, 5(4), 561-574.
Jin, J., & Shi, J. (1999). State space modeling of sheet metal assembly for dimensional control. Jour-nal of Manufacturing Science and Engineering, 121(4): 756-762.
John, B., & Kadadevarmath, R. (2015). A methodology for quantitatively managing the bug fixing process using Mahalanobis Taguchi system. Management Science Letters, 5(12), 1081-1090.
Montgomery, D. C. (2007). Introduction to statistical quality control. John Wiley & Sons.
Myatt, G. J. (2007). Making sense of data: a practical guide to exploratory data analysis and data min-ing. John Wiley & Sons.
Noghondarian, K., & Ghobadi, S. (2012). Developing a univariate approach to phase-I monitoring of fuzzy quality profiles. International Journal of Industrial Engineering Computations, 3(5), 829-842.
Neil, M. (1992). Multivariate assessment of software products. Softw. Test., Verif. Reliab., 1(4), 17-37.
Paulk, M. C. (1993). Comparing ISO 9001 and the capability maturity model for software. Software Quality Journal, 2(4), 245-256.
Pressman, R. S. (2005). Software engineering: a practitioner's approach. Palgrave Macmillan.
Samson, D., & Terziovski, M. (1999). The relationship between total quality management practices and operational performance. Journal of operations management, 17(4), 393-409.
Shu, L., & Tsung, F. (2003). On multistage statistical process control. Journal of the Chinese Institute of Industrial Engineers, 20(1), 1-8.
Shu, L., Apley, D. W., & Tsung, F. (2002). Autocorrelated process monitoring using triggered cuscore charts. Quality and Reliability Engineering International, 18(5), 411-421.
Shu, L., Tsung, F., & Kapur, K. C. (2004). Design of multiple cause-selecting charts for multistage processes with model uncertainty. Quality Engineering, 16(3), 437-450.
Shu, L., Tsung, F., & Tsui, K. L. (2005). Effects of estimation errors on cause-selecting charts. IIE transactions, 37(6), 559-567.
Song, Q., Shepperd, M., Cartwright, M., & Mair, C. (2006). Software defect association mining and defect correction effort prediction. IEEE Transactions on Software Engineering, 32(2), 69-82.
Tamura, S. (2009). CMMI and TSP/PSP: Using TSP Data to Create Process Performance Models.
Team, R. C. (2014). R: A language and environment for statistical computing. R Foundation for Sta-tistical Computing, Vienna, Austria. 2013.
Tsung, F., Li, Y., & Jin, M. (2008). Statistical process control for multistage manufacturing and ser-vice operations: a review and some extensions. International Journal of Services Operations and In-formatics, 3(2), 191-204.
Turhan, B., & Bener, A. (2007, October). A multivariate analysis of static code attributes for defect prediction. In Quality Software, 2007. QSIC'07. Seventh International Conference on (pp. 231-237). IEEE.
Zantek, P. F., Wright, G. P., & Plante, R. D. (2006). A self-starting procedure for monitoring process quality in multistage manufacturing systems. IIE Transactions, 38(4), 293-308.