Sensitivity analysis of software reliability metric estimator for Software Reliability Growth Models
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초록
When we estimate the parameters of software reliability models, we usually use maximum liklihood estimator(MLE). But this method is required a large data set. In particular, when we want to estimate it with small observed data such as early stages of testing, we give rise to the non-existence of MLE. Therefore, it is interesting to look into the influence of parameter estimators obtained using MLE. In this paper, we use two nonhomogenous poisson process software reliability growth model : delayed S-shaped model and log power model. In this paper, we calculate the sensitivity of estimators about failure intensity function for two SRGMs respectively.
Abstract
When we estimate the parameters of software reliability models, we usually use maximum liklihood estimator(MLE). But this method is required a large data set. In particular, when we want to estimate it with small observed data such as early stages of testing, we give rise to the non-existence of MLE. Therefore, it is interesting to look into the influence of parameter estimators obtained using MLE. In this paper, we use two nonhomogenous poisson process software reliability growth model : delayed S-shaped model and log power model. In this paper, we calculate the sensitivity of estimators about failure intensity function for two SRGMs respectively.
참고문헌 (15)
- Almering, V., "Using Software Reliability Growth Models in Practice", Software, IEEE, 24, pp.82~88 (2007)
- Charette, Robert N., "Why Software Fails?", Spectrum, IEEE, 42, pp.42~49 (2005)
- Cotte, D. W., "System-reliability confidenceintervals for complex-systems with estimated component-reliability", IEEE Transactions on Reliability, 46(4), pp.487~493 (1997)
- Dadkhah, "Foundations of Mathematical And Computational Economics, 1st Edition" (2007), South-Western Publisher
- Goel, A.L., "Software Relaibility Models: Assumptions, Limitations, and Applicability", IEEE Transactions Software Engineering, 11(12), pp.1411~1423 (1985)
- Goel, A.L., "Time-dependent error-detection rate model for software and other performance measures", IEEE Transactions on Reliability, R-28, pp.206~211 (1979)
- Hossain, S.A., "Estimating the parameters of a non-homogenous poisson process model for software reliability", IEEE Transactions on Reliability, R-42(4), pp.604~612 (1993)
- Huang, C.Y., "Optimal Software Release Policy Based on Cost, Reliability and Testing Efficiency", Proceedings of the 23rd Annual International Computer Software and Applications Conference, pp.468~473 (1999)
- Joe, H., "Statistical inference for general-orderstatistics and non homogenous Poisson process software reliability models", IEEE Transactions on software Engineering, 15(11), pp.1485~1490 (1989)
- Knafl, G.J., "Solving ML equations for 2-paremater Piosson-process models for ungrouped software-failure data", IEEE Transactions on Reliability, R-45(1), pp.42~53 (1996)
- Musa, J.D., "Software Reliability Engineering: More Reliable Software, Faster Development and Testing" (1998), McGraw-Hill
- Pham, H., "Software reliability assessment: Imperfect debugging and multiple failure types in software development,” EG&G-RAAM-10737", Idaho National Engineering Laboratory, ~
- Pham, H., "Software reliability" (2000), Springer-Verlag
- Yamada, S., "S-Shaped Reliability Growth Modeling for Software Error Detection", IEEE Transaction on Reliability, 32(5), pp.475~478 (1983)
- Zhao, M., "On the log-power software reliability model", Proceeding of the 3rd International Symposium on Software Reliability Engineering, pp.14~22 (1992)