Research Article
Time Domain based Software Process Control using Weibull Mean Value Function
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 18 - Issue 3 |
| Published: March 2011 |
| Authors: R.Satya Prasad, G.Krishna Mohan, R.R.L Kantham |
10.5120/2265-2916
|
R.Satya Prasad, G.Krishna Mohan, R.R.L Kantham . Time Domain based Software Process Control using Weibull Mean Value Function. International Journal of Computer Applications. 18, 3 (March 2011), 18-21. DOI=10.5120/2265-2916
@article{ 10.5120/2265-2916,
author = { R.Satya Prasad,G.Krishna Mohan,R.R.L Kantham },
title = { Time Domain based Software Process Control using Weibull Mean Value Function },
journal = { International Journal of Computer Applications },
year = { 2011 },
volume = { 18 },
number = { 3 },
pages = { 18-21 },
doi = { 10.5120/2265-2916 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2011
%A R.Satya Prasad
%A G.Krishna Mohan
%A R.R.L Kantham
%T Time Domain based Software Process Control using Weibull Mean Value Function%T
%J International Journal of Computer Applications
%V 18
%N 3
%P 18-21
%R 10.5120/2265-2916
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Control charts are widely used for process monitoring. Software reliability process can be monitored efficiently by using Statistical Process Control (SPC). It assists the software development team to identify failures and actions to be taken during software failure process and hence, assures better software reliability. In this paper we propose a control mechanism based on the cumulative quantity between observations of time domain failure data using mean value function of Weibull distribution, which is based on Non Homogenous Poisson Process (NHPP). The Maximum Likelihood Estimation (MLE) method is used to derive the point estimators of a two-parameter Weibull distribution.
References
- 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.
- 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.
- MacGregor, J.F., Kourti, T., 1995. “Statistical process control of multivariate processes”. Control Engineering Practice Volume 3, Issue 3, March 1995, Pages 403-414 .
- Musa, J.D., Iannino, A., Okumoto, k., 1987. “Software Reliability: Measurement Prediction Application”. McGraw-Hill, New York.
- Ohba, M., 1984. “Software reliability analysis model”. IBM J. Res. Develop. 28, 428-443.
- Pham. H., 1993. “Software reliability assessment: Imperfect debugging and multiple failure types in software development”. EG&G-RAAM-10737 Idaho National Engineering Laboratory.
- 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., “Some effective control chart procedures for reliability monitoring” -Reliability engineering and System Safety 77 143 -150¸ 2002.
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