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Monitoring Software Failure Process using Half Logistic Distribution

by R. Satya Prasad, K. Sowmya, R. Mahesh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 145 - Number 4
Year of Publication: 2016
Authors: R. Satya Prasad, K. Sowmya, R. Mahesh
10.5120/ijca2016910535

R. Satya Prasad, K. Sowmya, R. Mahesh . Monitoring Software Failure Process using Half Logistic Distribution. International Journal of Computer Applications. 145, 4 ( Jul 2016), 1-8. DOI=10.5120/ijca2016910535

@article{ 10.5120/ijca2016910535,
author = { R. Satya Prasad, K. Sowmya, R. Mahesh },
title = { Monitoring Software Failure Process using Half Logistic Distribution },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2016 },
volume = { 145 },
number = { 4 },
month = { Jul },
year = { 2016 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume145/number4/25263-2016910535/ },
doi = { 10.5120/ijca2016910535 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:47:50.854686+05:30
%A R. Satya Prasad
%A K. Sowmya
%A R. Mahesh
%T Monitoring Software Failure Process using Half Logistic Distribution
%J International Journal of Computer Applications
%@ 0975-8887
%V 145
%N 4
%P 1-8
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, Software reliability is the anticipation of operations which are free of error in the software in a stated environment during the detailed time duration. Statistical Process Control can survey the gauging of software failure and thereby devote significantly to the enhancement of software reliability. Such an assessment assists the software development team to pinpoint and diagnose their actions during software failure process and hence, assure superior software reliability. A control mechanism planted on the cumulative observations of interval domain failure data using mean value function of the Half Logistic Distribution (HLD) based on Non Homogeneous Poisson Process (NHPP) is proposed. The maximum likelihood estimation approach is used to estimate the unknown parameters of the model. A new mechanism is coded to analyze the observations instead of using regular control charts.

References
  1. N. Boffoli, G. Bruno, D. Cavivano, G. Mastelloni; Statistical process control for Software: a systematic approach; 2008 ACM 978-1-595933-971-5/08/10.
  2. K. U. Sargut, O. Demirors; Utilization of statistical process control (SPC) in emergent software organizations: Pitfallsand suggestions; Springer Science + Business media Inc. 2006.
  3. Burr,A. and Owen ,M.1996. Statistical Methods for Software quality .Thomson publishing Company.ISBN 1-85032-171-X.
  4. Carleton, A.D. and Florac, A.W. 1999. Statistically controlling the Software process. The 99 SEI Software Engineering Symposimn, Software Engineering Institute, Carnegie Mellon University.
  5. MacGregor, J.F., Kourti, T., 1995. “Statistical process control of multivariate processes”. Control Engineering Practice Volume 3, Issue 3, March 1995, Pages 403-414 .
  6. Wald, A.(1947). “Sequential Analysis”.Wiley, New York.
  7. Pham. H., 2006.“System software reliability”, Springer.
  8. E. E. Lewis, 1996 “Introduction to Reliability Engineering” John Wiley & Sons.
  9. Pham.H., 2003. “Handbook Of Reliability Engineering”, Springer.
  10. Xie, M., Goh. T.N., Ranjan.P., “Some effective control chart procedures for reliability monitoring” -Reliability engineering and System Safety 77 143 -150¸ 2002.
  11. MutsumiKomuro; Experiences of Applying SPC Techniques to software development processes; 2006 ACM 1-59593-085-x/06/0005.
  12. Ronald P.Anjard;SPC CHART selection process;Pergaman 0026-27(1995)00119-0Elsevier science ltd.
  13. Dr. R Satya Prasad ,K Ramchand H Rao and Dr. R.R. L Kantham (2011),” Software Reliability Measuring using Modified Maximum Likelihood Estimation and SPC” IJCA Journal, Number 7 – Article1
  14. R.Satya Prasad, Half Logistic Software Reliability Growth Model,Ph.D. Thesis,2007
  15. 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.
  16. Kimura, M., Yamada, S., Osaki, S., 1995. ”Statistical Software reliability prediction and its applicability based on mean time between failures”. Mathematical and Computer Modeling Volume 22, Issues 10-12, Pages 149-155.
  17. Koutras, M.V., Bersimis, S., Maravelakis,P.E., 2007. “Statistical process control using shewart control charts with supplementary Runs rules” Springer Science + Business media 9:207-224.
  18. Musa, J.D., Iannino, A., Okumoto, k., 1987. “Software Reliability: Measurement Prediction Application”. McGraw-Hill, New York.
  19. Ohba, M., 1984. “Software reliability analysis model”. IBM J. Res. Develop. 28, 428-443.
  20. Pham.H., 1993. “Software reliability assessment: Imperfect debugging and multiple failure types in software development”. EG&G-RAAM-10737 Idaho National Engineering Laboratory.
  21. Huang, C.Y. and Kuo, S.Y., (2003). “A unified scheme of some Nonhomogenous Poisson process models for software reliability estimation”, IEEE Transactions on Software Engineering, 29 (3): 261-269.
  22. ANSI/IEEE, (1991). "Standard Glossary of Software Engineering Terminology", STD-729-1991
  23. Ashoka. M., (2010). “Sonata software limited Data Set”, Bangalore.
  24. Baldassarre, M.T., Boffoli, N., Caivano, D. and Visaggio, G., (2004). “Managing software process improvement (SPI) through Statistical Process Control (SPC)”.In Proc.Of PROFES (kansai city Japan, 5-8. LNCS Springer, pp. 30-46.
  25. Caivano, D. (2005). “Continuous Software Process Improvement through Statistical Process Control”, Proceedings of the European conference of Software Maintanance and Reengineering-CSMR 05, IEEE Computer Society.
  26. https://msdn.microsoft.com/
  27. Card, D., (1994). “Statistical Process Control for Software”, IEEE Software, pp. 95-97.
  28. Chang, Y.P. (2001). “Estimation of Parameters for Non-homogeneous Poisson Process: Software Reliability with Change-point Model”, Communications in Statistics: Simulation and Computation, 30(3):625–635.
  29. “Reliability Engineering Handbook” By DodsoN/NolaN, CRC Press, 1999.
Index Terms

Computer Science
Information Sciences

Keywords

Statistical Process Control (SPC) Software reliability Probability limits HLD Maximum Likelihood Estimation Failure count data

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