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Different Ranking of NHPP Software Reliability Growth Models with Generalised Measure and Predictability

Nguyen Hung-cuong, Huynh Quyet-thang, Le Hai-trieu Published in Software Engineering

Different Ranking of NHPP Software Reliability Growth Models with Generalised Measure and Predictability
International Journal of Applied Information Systems
Year of Publication: 2014
© 2013 by IJAIS Journal
Series Volume 7 Number 11
Authors Nguyen Hung-cuong, Huynh Quyet-thang, Le Hai-trieu
10.5120/ijais14-451257
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  1. Nguyen Hung-cuong, Huynh Quyet-thang and Le Hai-trieu. Article: Different Ranking of NHPP Software Reliability Growth Models with Generalised Measure and Predictability. International Journal of Applied Information Systems 7(11):1-6, November 2014. BibTeX

    @article{key:article,
	author = "Nguyen Hung-cuong and Huynh Quyet-thang and Le Hai-trieu",
	title = "Article: Different Ranking of NHPP Software Reliability Growth Models with Generalised Measure and Predictability",
	journal = "International Journal of Applied Information Systems",
	year = 2014,
	volume = 7,
	number = 11,
	pages = "1-6",
	month = "November",
	note = "Published by Foundation of Computer Science, New York, USA"
}

Abstract

In recent years, the authors have proposed a number of Nonhomogeneous Poisson process (NHPP) software reliability growth models (SRGMs) to analyse and measure the growth of software reliability during production process. This study works with a mathematics methodology to evaluate and then rank some basic NHPP SRGMs. Characteristics of ranking are: the fit of calculated occurrence failure times with real occurrence failure times; and the fit of a predicted time of the next failure with a real one. From a set of individual measures, the methodology mentioned will be deployed. The implementation of some SRGMs with several real data sets confirms that the ranking of SRGMs depends on the data sets.

Reference

  1. H. Pham, System software reliability. Springer, 2006.
  2. A. L. Goel and K. Okumoto, "Time-dependent errordetection rate model for software reliability and other performance measures," Reliability, IEEE Transactions on, vol. 28, no. 3, pp. 206–211, 1979.
  3. S. Yamada, M. Ohba, and S. Osaki, "S-shaped software reliability growth models and their applications," Reliability, IEEE Transactions on, vol. 33, no. 4, pp. 289–292, 1984.
  4. J. D. Musa and K. Okumoto, "A logarithmic poisson execution time model for software reliability measurement," in Proceedings of the 7th international conference on Software engineering, pp. 230–238, IEEE Press, 1984.
  5. M. Lefebvre, Applied probability and statistics. Springer, 2006.
  6. M. Anjum, M. A. Haque, N. Ahmad, et al. , "Analysis and ranking of software reliability models based on weighted criteria value," International Journal of Information Technology and Computer Science, vol. 2, no. 1, 2013.
  7. M. Ohba, "Software reliability analysis models," IBM Journal of research and Development, vol. 28, no. 4, pp. 428– 443, 1984.

Keywords

Software Reliability Modelling, Non-homogeneous Poisson Process, Probability Distribution