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The Comparative Study for the Property of Learning Effect based on Delay ed Software S-Shaped Reliability Model  

Kim, Hee-Cheul (남서울대학교 산업경영공학과)
Shin, Hyun-Cheul (백석문화대학 인터넷정보학부)
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Abstract
In this study, software products developed in the course of testing, software managers in the process of testing software and tools for effective learning effects perspective has been studied using the NHPP software. The delayed software S-shaped reliability model applied to distribution was based on finite failure NHPP. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R^2$(coefficient of determination).
Keywords
Learning Effects; Non-Homogeneous Poisson Process; Delayed Software S-shaped Reliability;
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1 Shyur H-J. "A stochastic software reliability model with imperfect debugging and change-point", J Syst. Software 66, pp.135-141, 2003.   DOI   ScienceOn
2 Pham H, Zhang X. "NHPP software reliability and cost models with testing coverage", Eur J Oper Res, 145, pp.445-454, 2003.
3 Huang C-Y. "Performance analysis of software reliability growth models with testing-effort and change-point". J Syst Software 76, pp. 181-194, 2005.   DOI   ScienceOn
4 Kuei-Chen, C., Yeu-Shiang, H., and Tzai-Zang, L. "A study of software reliability growth from the perspective of learning effects". Reliability Engineering and System Safety 93, pp. 1410- .14 21, 2008.   DOI   ScienceOn
5 J. F. Lawless. Statistical Models and Methods for Lifetime Data. John Wiley & Sons, New York, 1981.
6 L. Kuo and T. Y. Yang."Bayesian Computation of Software Reliability".Journal of the American Statistical Association, Vol.91, pp. 763-773, 1996.   DOI   ScienceOn
7 Alaa Sheta, "Parameter Estimation of Software Reliability Growth Models by Particle S warm Optimization", AIML Journal, Volume (7), Issue (1), pp. 55-61, June, 2007.
8 Y. HAYAKAWA and G. TELFAR "Mixed Poisson-Type Processes with Application in Software Reliability", Mathematical and Computer Modelling, 31, pp. 151-156, 2000.   DOI   ScienceOn
9 K. Kanoun and J. C. Laprie, "Handbook of Software Reliability Engineering", M.R.Lyu, Editor, chapter Trend Analysis. McGraw-Hill New York, NY: 1996; p.401-437.
10 Gokhale, S. S. and Trivedi, K. S. "A time/ structure based software reliability model", Annals of Software Engineering. 8, pp. 85-121. 1999.   DOI   ScienceOn
11 Goel AL, Okumoto K, " Time-dependent fault detection rate model for software and other performance measures", IEEE Trans Reliab 28, pp.206-11, 1978.
12 Yamada S, Ohba H. " S-shaped software reliability modeling for software error detection", IEEE Trans Reliab, 32, pp.475-484, 1983.
13 Zhao M. "Change-point problems in software and hardware reliability", Commun. Stat Theory Methods,22(3), pp.757-768, 1993.   DOI   ScienceOn