On a cost and availability analysis for software systems via phase type non-homogeneous Poisson process

References

• Chatterjee, S., and A. Shukla. 2017. An ideal software release policy for an improved software reliability growth model incorporating imperfect debugging with fault removal efficiency and change point. Asia-Pacific Journal of Operational Research 34 (03):1740017. doi: 10.1142/S0217595917400176.
   Google Scholar
• Dai, Y. S., M. Xie, K. L. Poh, and G. Q. Liu. 2003. A study of service reliability and availability for distributed systems. Reliability Engineering & System Safety 79 (1):103–12. doi: 10.1016/S0951-8320(02)00200-4.
   Web of Science ®Google Scholar
• Das, S., D. Kundu, and A. Dewanji. 2022. Software reliability modelling based on NHPP for error occurrence in each fault with periodic debugging schedule. Communications in Statistics – Theory and Methods 51 (14):4890–902. doi: 10.1080/03610926.2020.1828462.
   Web of Science ®Google Scholar
• Goel, A. L., and K. Okumoto. 1979. Time-dependent error-detection rate model for software reliability and other performance measures. IEEE Transactions on Reliability 28:206–11. doi: 10.1109/TR.1979.5220566.
   Web of Science ®Google Scholar
• Huang, C. Y., and M. R. Lyu. 2005. Optimal release time for software systems considering cost, testing-effort, and test efficiency. IEEE Transactions on Reliability 54 (4):583–91. doi: 10.1109/TR.2005.859230.
   Web of Science ®Google Scholar
• Khoshgoftaar, T. M. 1988. Non-homogeneous Poisson processes for software reliability growth. In Proceedings of the International Conference on Computational Statistics (COMPSTAT), 13–4, Copenhagen, Denmark.
   Google Scholar
• Lai, C. D., M. Xie, K. L. Poh, Y. S. Dai, and P. Yang. 2002. A model for availability analysis of distributed software/hardware systems. Information and Software Technology 44 (6):343–50. doi: 10.1016/S0950-5849(02)00007-1.
   Web of Science ®Google Scholar
• Langberg, N., and N. D. Singpurwalla. 1985. Unification of some software reliability models. SIAM Journal on Scientific and Statistical Computing 6 (3):781–90. doi: 10.1137/0906053.
   Web of Science ®Google Scholar
• Laprie, J. C., K. Kanoun, C. Béounes, and M. Kaâniche. 1991. The KAT (knowledge-action – transformation) approach to the modelling and evaluation of reliability and availability growth. IEEE Transactions on Software Engineering 17 (4):370–82. doi: 10.1109/32.90436.
   Web of Science ®Google Scholar
• Lee, C. H., S. M. Lee, and D. H. Park. 2005. Evaluation of software availability for the imperfect software debugging model. International Journal of Systems Science 36 (11):671–8. doi: 10.1080/00207720500159904.
   Web of Science ®Google Scholar
• Li, X., M. Xie, and S. H. Ng. 2010. Sensitivity analysis of release time of software reliability models incorporating testing effort with multiple change-points. Applied Mathematical Modelling 34 (11):3560–70. doi: 10.1016/j.apm.2010.03.006.
   Web of Science ®Google Scholar
• Musa, J. D. 1999. Software reliability engineering. New York: McGraw-Hill.
   Google Scholar
• Nguyen, H. C., and Q. Huynh. 2022. New non-homogeneous Poisson process software reliability model based on a 3-parameter S-shaped function. IET Software 16 (2):214–32. doi: 10.1049/sfw2.12055.
   Web of Science ®Google Scholar
• Neuts, M. F. 1975. Probability distributions of phase type. Belgium: Liber Amicorum Professor Emeritus H. Florin Department of Mathematics University of Louvain.
   Google Scholar
• Neuts, M. F. 1981. Matrix geometric solutions in stochastic models: An algorithmic approach. Baltimore: The John Hopkins University Press.
   Google Scholar
• Okamura, H., and T. Dohi. 2006. Building phase-type software reliability model. In Proceedings of the 17th International Symposium on Software Reliability Engineering (ISSRE), Raleigh, NC, 289–98.
   Google Scholar
• Okamura, H., and T. Dohi. 2008. Hyper-Erlang software reliability model. Proceedings of the 14th Pacific Rim International Symposium on Dependable Computing (PRDC), Taipei, Taiwan, 232–239.
   Google Scholar
• Okamura, H., T. Dohi, and S. Osaki. 2013. Software reliability growth models with normal failure timedistributions. Reliability Engineering & System Safety 116:135–41. doi: 10.1016/j.ress.2012.02.002.
   Web of Science ®Google Scholar
• Pham, H. 1999. Software reliability. In Wiley Encyclopedia of Electrical and Electronics Engineering, J.G. Webster (Ed.). doi: 10.1002/047134608X.W6952.
   Google Scholar
• Prince Williams. D. R. 2007. Study of the warranty cost model for software reliability with an imperfect debugging phenomenon. Turkish Journal of Electrical Engineering and Computer Sciences 15:369–81.
   Google Scholar
• Ross, S. M. 1996. Stochastic processes. 2nd ed. New York: Wiley.
   Google Scholar
• Sarada, Y., and R. Shenbagam. 2015. On warranty cost analysis using alternating phase type quasi-renewal processes. International Journal of Reliability, Quality and Safety Engineering 22 (06):1550026. doi: 10.1142/S0218539315500266.
   Google Scholar
• Sarada, Y., and R. Shenbagam. 2019. On warranty cost analysis for software reliability model via phase-type distribution. Reliability: Theory and Applications Electronic Journal of International Group on Reliability 14:1932–2321.
   Google Scholar
• Shanthikumar, J. G. 1984. On a software availability model with imperfect maintenance. Operations Research Letters 2:285–90.
   Web of Science ®Google Scholar
• Shrivastava, A. K., and R. Sharma. 2022. Developing a hybrid software reliability growth model. International Journal of Quality & Reliability Management 39 (5):1209–225.
   Web of Science ®Google Scholar
• Taha, H. A. 1989. Operations research: An introduction. 4th ed. New York: Macmillan.
   Google Scholar
• Tokuno, K., and S. Yamada. 1995. A Markovian software availability measurement with a geometrically decreasing failure-occurrence rate. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E78-A:737–41.
   Google Scholar
• Tokuno, K., and S. Yamada. 2001. Markovian modelling or software availability analysis under intermittent use. International Journal of Reliability, Quality and Safety Engineering 08 (03):249–58.
   Google Scholar
• Tokuno, K., and S. Yamada. 2011. Codesign-oriented performability modelling for hardware-software systems. IEEE Transactions on Reliability 60 (1):171–9.
   Web of Science ®Google Scholar
• Wang, H., and H. Pham. 2009. Quasi-renewal time delay fault removal consideration in Software reliability modelling. IEEE Transactions on Systems, Man and Cybernetics Part A: Systems and Humans 39:200–9.
   Web of Science ®Google Scholar
• Wang, J., Z. Wu, Y. Shu, and Z. Zhang. 2016. An optimized methods for software reliability model based on nonhomogeneous Poisson process. Applied Mathematical Modelling 40 (13-14):6324–339.
   Web of Science ®Google Scholar
• Xie, M. 1991. Software reliability modelling. Singapore: World Scientific.
   Google Scholar
• Yamada, S. 1994. Optimal release problems with warranty period based on a software maintenance cost model. Transactions of the Information Processing Society of Japan 35: 2197–2202.
   Google Scholar
• Yamada, S., and T. Fujiwara. 2001. Testing – domain dependent software reliability growth models and their comparisons of goodness-of-fit. International Journal of Reliability, Quality and Safety Engineering 08 (03):205–18.
   Google Scholar
• Yamada, S., M. Ohba, and S. Osaki. 1983. S-shaped reliability growth modelling for software error detection. IEEE Transactions on Reliability 32:475–8.
   Web of Science ®Google Scholar
• Zhang, X., and H. Pham. 1998. A software cost model with warranty cost, error removal times and risk costs. IIE Transactions 30 (12):1135–42.
   Web of Science ®Google Scholar
• Zhao, M., and M. Xie. 1996. On maximum likelihood estimation for a general non-homogeneous Poisson process. Scandinavian Journal of Statistics 23:597–607.
   Web of Science ®Google Scholar