CFP last date
20 January 2025
Reseach Article

Software Reliability Growth Modeling with New Modified Weibull Testingñeffort and Optimal Release Policy

by S. M. K. Quadri, N. Ahmad
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 6 - Number 12
Year of Publication: 2010
Authors: S. M. K. Quadri, N. Ahmad
10.5120/1127-1477

S. M. K. Quadri, N. Ahmad . Software Reliability Growth Modeling with New Modified Weibull Testingñeffort and Optimal Release Policy. International Journal of Computer Applications. 6, 12 ( September 2010), 1-10. DOI=10.5120/1127-1477

@article{ 10.5120/1127-1477,
author = { S. M. K. Quadri, N. Ahmad },
title = { Software Reliability Growth Modeling with New Modified Weibull Testingñeffort and Optimal Release Policy },
journal = { International Journal of Computer Applications },
issue_date = { September 2010 },
volume = { 6 },
number = { 12 },
month = { September },
year = { 2010 },
issn = { 0975-8887 },
pages = { 1-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume6/number12/1127-1477/ },
doi = { 10.5120/1127-1477 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:55:09.950815+05:30
%A S. M. K. Quadri
%A N. Ahmad
%T Software Reliability Growth Modeling with New Modified Weibull Testingñeffort and Optimal Release Policy
%J International Journal of Computer Applications
%@ 0975-8887
%V 6
%N 12
%P 1-10
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In software development life cycle, software testing is one of the most important tasks; and in the testing, software reliably is very important aspect for any category of software systems. A number of testing-effort functions for software reliability growth model based on non-homogeneous Poisson process (NHPP) have been proposed in the past. Although these models are quite helpful for software developers and have been widely accepted and applied in the industries and research centers, we still need to put more testing-effort functions into software reliability growth model for accuracy on estimate of the parameters. In this paper, we will consider the case where the time dependent behaviors of testing-effort expenditures are described by New Modified Weibull Distribution (NMWD). Software Reliability Growth Models (SRGM) based on the NHPP are developed which incorporates the (NMWD) testing-effort expenditure during the software- testing phase. It is assumed that the error detection rate to the amount of testing-effort spent during the testing phase is proportional to the current error content. Model parameters are estimated by Least Square and Maximum Likelihood estimation techniques, and software measures are investigated through numerical experiments on real data from various software projects. The evaluation results are analyzed and compared with other existing models to show that the proposed SRGM with (NMWD) testing-effort has a fairly better faults prediction capability and it depicts the real-life situation more faithfully. This model can be applied to a wide range of software system. In addition, the optimal release policy for this model, based on reliability criterion is discussed.

References
  1. Ahmad, N., Khan, M. G. M., Quadri, S. M. K. and Kumar, M., “Modeling and Analysis of Software Reliability with Burr Type X Testing-Effort and Release-Time Determination”, Journal of Modeling in Management, Vol. 4 (1), 28 – 54, 2009.
  2. Ahmad, N., Bokhari, M. U., Quadri, S. M. K. and Khan, M. G. M. (2008), “The Exponetiated Weibull Software Reliability Growth Model with various testing-efforts and optimal release policy: a performance analysis”, International Journal of Quality and Reliability Management, Vol. 25 (2), pp. 211-235.
  3. Goel, A.L. and Okumoto, K., “Time dependent error-detection rate model for software reliability and other performance measures“, IEEE Transactions on Reliability, Vol. R- 28, No. 3, pp. 206-211, 1979.
  4. Huang, C. Y. “Cost-reliability-optimal-release policy for software reliability models incorporating improvements in testing efficiency“, Journal of Systems and Software 77(2), pp. 139-155, 2005b.
  5. Huang, C.Y. and Kuo, S. Y. ”, Analysis of incorporating logistic testing-effort function into software reliability modeling“, IEEE Transactions on Reliability, Vol. 51, no. 3, pp. 261-270, 2002.
  6. Huang, C. Y. “Performance analysis of software reliability growth models with testing-effort and change-point“, Journal of Systems and Software, Vol. 76, pp. 181-194, 2005.
  7. Huang, C. Y., Kuo, S.Y. and Lyu, M. R. , “Optimal software release policy based on cost, reliability and testing efficiency“, Proceedings of the 23rd IEEE Annual International Computer Software and Applications Conference (COMPSAC’99), Phoenix, Arizona, pp. 468-473, 1999.
  8. Huang, C. Y., Kuo, S.Y. and Lyu, M. R. , “Effort-index based software reliability growth models and performance assessment“, Proceedings of the 24th IEEE Annual International Computer Software and Applications Conference (COMPSAC’2000), pp. 454-459, 2000.
  9. Huang, C.Y., Kuo, S.Y. and Chen, I.Y., “Analysis of software reliability growth model with logistic testing-effort function“, Proceeding of 8th International Symposium on Software Reliability Engineering (ISSRE’1997), Albuquerque, New Maxico, pp. 378-388, 1997.
  10. Kapur, P. K. and Bhalla, V. K., “Optimal Release Policy for Flexible Software Reliability Growth Model”, Engineering and System Safety, Vol. 35, pp. 49-54, 1992.
  11. Kapur, P.K. and Garg, R.B., “Cost reliability optimum release policies for a software system with testing effort“, Operations Research, Vol. 27, no. 2, pp. 109-116, 1990.
  12. Kapur, P.K. and Garg, R.B. “Modeling an imperfect debugging phenomenon in software reliability“, Microelectronics and Reliability, Vol. 36, pp. 645-650, 1996.
  13. Kapur, P.K. and Younes, S., “Modeling an imperfect debugging phenomenon with testing effort“, Proceedings of 5th International Symposium on Software Reliability Engineering (ISSRE’1994), pp. 178-183, 1994.
  14. Kapur, P.K., Garg, R.B. and Kumar, S., Contributions to Hardware and Software Reliability, World Scientific, Singapore, 1999.
  15. Kumar, M., Ahmad, N. and Quadri, S.M.K., “Software reliability growth models and data analysis with a Pareto test-effort“, RAU Journal of Research, Vol., 15 (1-2), pp. 124-128, 2005.
  16. Kuo, S.Y., Hung, C.Y. and Lyu, M.R., “Framework for modeling software reliability, using various testing-efforts and fault detection rates“, IEEE Transactions on Reliability, Vol. 50, no.3, pp 310-320, 2001.
  17. Lyu, M.R., Handbook of Software Reliability Engineering, McGraw- Hill, 1996.
  18. Musa J. D, Software Reliability Engineering: More Reliable Software, Faster Development and Testing, McGraw-Hill, 1999.
  19. Musa, J.D., Iannino, A. and Okumoto, K., Software Reliability: Measurement, Prediction and Application, McGraw-Hill, 1987.
  20. Ohba, M., “Software reliability analysis model” IBM Journal. Research Development, Vol. 28, no. 4, pp. 428-443, 1984.
  21. Okumoto, K. and Goel, A. L., “Optimum release time for software system based on reliability and cost criteria”, Journal of Systems and Software, Vol.1, pp. 315-318, 1980.
  22. Pham, H. (2000), Software Reliability, Springer-Verlag, New York, 2000.
  23. Putnam, L., “A general empirical solution to the macro software sizing and estimating problem“, IEEE Transactions on Software Engineering, Vol. Se-4, pp. 343-361, 1978.
  24. Quadri, S. M. K., Ahmad, N., Peer, M.A. and Kumar, M., “Non homogeneous Poisson process Software Reliability Growth Model with generalized exponential testing effort function, “RAU Journal of Research, Vol., 16 (1-2), pp. 159-163, 2006.
  25. Tang, Y. et. al. “Statistical Analysis of a Weibull Extension Model”, Communications in Statistics, Theory and Analysis, pp. 911-916, 2003.
  26. Tian, J., Lu, P., and Palma, J., “Test-Execution-Based Reliability Measurement and Modeling for Large Commercial Software”, IEEE Transaction Software Engineering, Vol. 21, No. 5, pp. 405-414, 1995.
  27. Tohma, Y., Jacoby, R., Murata, Y. and Yamamoto, M., “Hyper-geometric distribution model to estimate the number of residual software fault“, Proceeding of COMPSAC-89, Orlando, pp. 610-617, 1989.
  28. Xie, M., “On the determination of optimum software release time”. In Proceeding 2nd International Symposium on software reliability engineering, pp. 218-224, 1991a.
  29. Yamada, S. and Ohtera, H., “Software reliability growth models for testing effort control“, European Journal of Operational Research, Vol. 46, no. 3, pp. 343-349. 1990.
  30. Yamada, S. and Osaki, S., “Cost-reliability optimal release policies for software systems“, IEEE Transaction on Reliability, Vol. R-34, no. 5, pp. 422-424, 1985b.
  31. Yamada, S., and Osaki, S., “Software reliability growth modeling: models and applications“, IEEE Transaction on Software Engineering, Vol. SE-11, no. 12, pp. 1431-1437, 1985a.
  32. Yamada, S., Hishitani J. and Osaki, S., “Test-effort dependent software reliability measurement, “ International Journal of Systems Science, Vol. 22, no. 1, pp. 73-83, 1991.
  33. Yamada, S., Hishitani J. and Osaki, S., “Software reliability growth model with Weibull testing-effort: a model and application“, IEEE Transactions on Reliability, Vol. R-42, pp. 100-105, 1993.
  34. Yamada, S., Narihisa, H. and Osaki, S., “Optimum release policies for a software system with a scheduled software delivery time“, International Journal of System Science, Vol.15, pp. 905-914, 1984.
  35. Yamada, S., Ohtera, H. and Narihisa, H., “A testing-effort dependent software reliability model and its application“, Microelectronics and Reliability, Vol. 27, no. 3, pp. 507-522, 1987.
  36. Yamada, S., Ohtera, H. and Norihisa, H. , “Software reliability growth model with testing-effort“, IEEE Transactions on Reliability, Vol. R-35, no. 1, pp.19-23, 1986.
Index Terms

Computer Science
Information Sciences

Keywords

Software reliability growth model Optimal software release policy Estimation method Testing-effort function Mean value function Non-homogeneous Poisson process