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The Comparative Study for NHPP Software Reliability Model based on the Property of Learning Effect of Log Linear Shaped Hazard Function  

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 log type hazard function 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 autonomous errors-detected factor that is generally efficient model could be confirmed. This paper, a failure data analysis 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; Log Shaped Type Hazard function;
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1 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.
2 Hee-Cheul Kim and Hyoung-Keun Park. "The Comparative Study for ENHPP Software Reliability Growth Model Based on Mixture Coverage Function". Communications in Computer and Information Science, Springer-Verlag Berlin, Heidelberg. pp. 187-194, 2011
3 김희철, 신현철"학습효과 기법을 이용한 NHPP 소프트웨어 신뢰도 모형에 관한 연구 ", 정보, 보안 논문지, 제11권 3호, pp. 26-32, 2011년 3월
4 Gokhale, S. S. and Trivedi, K. S. "A tim e/structure based software reliability mode l", Annals of Software Engineering. 8, pp. 85-121. 1999.   DOI   ScienceOn
5 Goel AL, Okumoto K, " Time-dependent fault detection rate model for software and other performance measures", IEEE Trans Reliab 28, pp.206-11, 1978.
6 Yamada S, Ohba H. " S-shaped software reliability modeling for software error detection", IEEE Trans Reliab, 32, pp.475-484, 1983.
7 Zhao M. "Change-point problems in softwa re and hardware reliability", Commun. Stat Theory Methods, 22(3), pp.757-768, 1993.   DOI   ScienceOn
8 Shyur H-J. "A stochastic software reliabilit y model with imperfect debugging and change-point", J Syst. Software 66, pp.135-141, 2003.   DOI   ScienceOn
9 Pham H, Zhang X. "NHPP software reliabil ity and cost models with testing coverage ", Eur J Oper Res, 145, pp.445-454, 2003.
10 Huang C-Y. "Performance analysis of soft ware reliability growth models with testing -effort and change-point". J Syst Software 76, pp. 181-194, 2005.   DOI   ScienceOn
11 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. 1410-1421, 2008.   DOI   ScienceOn
12 J. F. Lawless. Statistical Models and Methods for Lifetime Data. John Wiley & Sons, New York, 1981.
13 L. Kuo and T. Y. Yang."Bayesian Comput ation of Software Reliability". Journal of the American Statistical Association, Vol.91, pp. 763-773, 1996.   DOI   ScienceOn
14 Alaa Sheta, "Parameter Estimation of Software Reliability Growth Models by Particle Swarm Optimization", AIML Journal, Volume (7), Issue (1), pp. 55-61, June, 2007.
15 Y. HAYAKAWA and G. TELFAR "Mixe d Poisson-Type Processes with Application in Software Reliability", Mathematical and Computer Modelling, 31, pp. 151-156, 2000.   DOI   ScienceOn