Advanced SearchSearch Tips
The Study for Performance Analysis of Software Reliability Model using Fault Detection Rate based on Logarithmic and Exponential Type
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
The Study for Performance Analysis of Software Reliability Model using Fault Detection Rate based on Logarithmic and Exponential Type
Kim, Hee-Cheul; Shin, Hyun-Cheul;
  PDF(new window)
Software reliability in the software development process is an important issue. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, reliability software cost model considering logarithmic and exponential fault detection rate based on observations from the process of software product testing was studied. Adding new fault probability using the Goel-Okumoto model that is widely used in the field of reliability problems presented. When correcting or modifying the software, finite failure non-homogeneous Poisson process model. For analysis of software reliability model considering the time-dependent fault detection rate, the parameters estimation using maximum likelihood estimation of inter-failure time data was made. The logarithmic and exponential fault detection model is also efficient in terms of reliability because it (the coefficient of determination is 80% or more) in the field of the conventional model can be used as an alternative could be confirmed. From this paper, the software developers have to consider life distribution by prior knowledge of the software to identify failure modes which can be able to help.
Software Reliability;NHPP;Logarithmic and exponential fault detection;Laplace trend test;
 Cited by
Gokhale, S. S. and Trivedi, K. S. A, "time/structure based software reliability model", Annals of Software Engineering. 8, pp. 85-121. 1999. crossref(new window)

Goel A L, Okumoto K, "Time-dependent fault detection rate model for software and other performance measures", IEEE Trans. Reliab. 28, pp. 206-11, 1978.

Hee-Cheul KIM, "The Assessing Comparative Study for Statistical Process Control of Software Reliability Model Based on Rayleigh and Burr Type", Journal of korea society of digital industry and information management, Volume 10, No.2, pp. 1-11. 2014. crossref(new window)

K,H Rao, R. S, Prasad and. R.L.Kantham "Software Reliability Measuring using Modified Maximum Likelihood Estimation and SPC", International Journal of Computer Applications(0975-8887), Volume 21, No.7, pp. 1-5., May 2011.

Tae-Hyun Yoo, "The Infinite NHPP Software Reliability Model based on Monotonic Intensity Function", Indian Journal of Science and Technology, Vol. 8, No. 14, pp. 1-7, 2015.

K. Kanoun and J. C. Laprie, "Handbook of Software Reliability Engineering", M.R.Lyu, Editor, chapter Trend Analysis. McGraw-Hill New York, NY, pp. 401-437, 1996.

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. crossref(new window)

J. F. Lawless. Statistical Models and Methods for Life time Data. John Wiley & Sons, New York, 1981.

Kuo L, Yang TY,. "Bayesian computation of software reliability" .Journal of the American Statistical Association. Vol.. 91, pp.763-773,, 1999.

Kim H-C. The Property of Learning effect based on Delayed Software S-Shaped Reliability Model using Finite NHPP Software Cost Model, Indian Journal of Science and Technology 8(34), pp.1-7, 2015.