Burr Type XII Software Reliability Growth Model
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10.5120/18995-0452 |
R.satya Prasad, K.v.murali Mohan and G.sridevi. Article: Burr Type XII Software Reliability Growth Model. International Journal of Computer Applications 108(16):16-20, December 2014. Full text available. BibTeX
@article{key:article,
author = {R.satya Prasad and K.v.murali Mohan and G.sridevi},
title = {Article: Burr Type XII Software Reliability Growth Model},
journal = {International Journal of Computer Applications},
year = {2014},
volume = {108},
number = {16},
pages = {16-20},
month = {December},
note = {Full text available}
}
Abstract
Software Reliability Growth model (SRGM) is a mathematical model of how the software reliability improves as faults are detected and repaired. The development of many SRGMs over the last several decades have resulted in the improvement of software facilitating many engineers and managers in tracking and measuring the growth of reliability. This paper proposes Burr type XII based Software Reliability growth model with time domain data. The unknown parameters of the model are estimated using the maximum likelihood (ML) estimation method. Reliability of a software system using Burr type XII distribution, which is based on Non-Homogenous Poisson process (NHPP), is presented through estimation procedures. The performance of the SRGM is judged by its ability to fit the software failure data. How good does a mathematical model fit to the data is also being calculated. To access the performance of the considered SRGM, we have carried out the parameter estimation on the real software failure datasets.
References
- Kimura, M. , Yamada, S. , Osaki, S. , 1995. "Statistical Software reliability prediction and its applicability based on mean time between failures". Mathematical and Computer Modelling Volume 22, Issues 10-12, Pages 149-155.
- Ashoka, M. , (2010), "Sonata Software Limited" data set, Bangalore.
- Lyu, M. R. , (1996), "Handbook of Software Reliability Engineering", MCGraw-Hill, New York.
- Musa, J. D. , Iannino, A. , Okumoto, k. , 1987. "Software Reliability: Measurement Prediction Application". McGraw -Hill, New York.
- Hee-cheul Kim. , "Assessing Software Reliability based on NHPP using SPC", International Journal of Software Engineering and its Applications, vol. 7,No. 6 (2013), pp. 61-70.
- Pham. H. , 2003. "Handbook of Reliability Engineering", Springer.
- Pham. H. , 2006. "System software reliability", Springer.
- Swapna S. Gokhale and Kishore S. Trivedi, 1998. "Log-Logistic Software Reliability Growth Model". The 3rd IEEE International Symposium on High-Assurance Systems Engineering. IEEE Computer Society.
- Xie, M. , Goh. T. N. , Ranjan. P. , (2002) "Some effective control chart procedures for reliability monitoring" – Reliability engineering and System Safety 77 143 -150 ? 2002.
- Satya Prasad, R. , "Half logistic distribution for software reliability growth model", Ph. D thesis, 2007.
- Goel, A. L. , Okumoto, K. , 1979. Time-dependent error detection rate model for software reliability and other performance measures. IEEE Trans. Reliab. R-28, 206-211.
- Satya Prasad, R. , Shaheen. , Krishna Mohan, G. , "Two step Approach for Software reliability: HLSRGM", IJCTT-Volume 4 Issue 10-Oct 2013.
- Wood, A. , (1996), "Software Reliability Growth models", Tandem Computers, Technical report 96. 1.
- Quadri, S. M. K and Ahmad, N. , (2010), "Software Reliability Growth Modelling with new modified Weibull testing-effort and optimal release policy", International Journal of Computer Applications, Vol. 6, No. 12.
- Xie, M. , Yang, B. and Gaudoin, O. (2001), "Regression goodness-of-fit Test for Software reliability model validation ", ISSRE and Chillarege Corp.