CFP last date
22 April 2024
Reseach Article

Software Reliability Measurement and Improvement Policies

Published on February 2013 by Sargun Toor, Kailash Bahl
International Conference on Advances in Management and Technology 2013
Foundation of Computer Science USA
ICAMT - Number 1
February 2013
Authors: Sargun Toor, Kailash Bahl
ba903d3a-6d29-4b72-b91c-3e219b2dae97

Sargun Toor, Kailash Bahl . Software Reliability Measurement and Improvement Policies. International Conference on Advances in Management and Technology 2013. ICAMT, 1 (February 2013), 41-44.

@article{
author = { Sargun Toor, Kailash Bahl },
title = { Software Reliability Measurement and Improvement Policies },
journal = { International Conference on Advances in Management and Technology 2013 },
issue_date = { February 2013 },
volume = { ICAMT },
number = { 1 },
month = { February },
year = { 2013 },
issn = 0975-8887,
pages = { 41-44 },
numpages = 4,
url = { /proceedings/icamt/number1/10841-1024/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advances in Management and Technology 2013
%A Sargun Toor
%A Kailash Bahl
%T Software Reliability Measurement and Improvement Policies
%J International Conference on Advances in Management and Technology 2013
%@ 0975-8887
%V ICAMT
%N 1
%P 41-44
%D 2013
%I International Journal of Computer Applications
Abstract

This paper discusses about various aspects of software reliability. Software reliability is the probability of the failure free operation of a computer program for a specified period of time in a specified environment. Although Software Reliability is defined as a probabilistic function, and comes with the notion of time, different from traditional Hardware Reliability, Software Reliability is not a direct function of time. Electronic and mechanical parts may become "old" and wear out with time and usage, but software will not rust or wear-out during its life cycle. Reliability measures the probability of failure, not the consequences of those failures. Software Reliability is dynamic and stochastic. This article provides an overview of Software Reliability measurement and improvement policies then examines different improvement policies for software reliability, however, there is no single model that is universal to all the situations.

References
  1. Aasia Quyoum, Mehraj – Ud - Din Dar, M. K. Quadri Di. "Improving Software Reliability using Software Engineering Approach- A Review", International Journal of Computer Applications (0975 – 8887)Volume 10– No. 5, November 2010.
  2. C. Y. Huang, M. R. Lyu, and S. Y. Kuo, "A Unified Scheme of Some Non-Homogeneous Poisson Process Models for Software Reliability Estimation," IEEE Transactions on Software Engineering, vol. 29, no. 3, March 2003, pp. 261-269.
  3. Doron A Peled. Software Reliability Methods. Springer, 2001.
  4. E Eduardo Valido-Cabrera, "Software reliability methods", Technical University of Madrid August, 2006.
  5. E. Valido-Cabrera, "Software Reliability Methods," Technical Report, Technical University of Madrid, 2006.
  6. Goutam Kumar Saha, "Software Reliability Issues: Concept Map", IEEE Reliability Society 2009 Annual Technology Report.
  7. Michael R. Lyu, "Software Reliability Engineering: A Roadmap".
  8. Allen P. Nilora, Jet Propulsion Laboratory, California Institute of Technology.
  9. Alen Wood, "Software Reliability Growth Models", Technical Report96. 1 September1996 Part Number:130056.
  10. Jiantao Pan, "Software Reliability", 18-849b Dependable Embedded Systems, CMU, 1999.
  11. Musa, Iannino and Okumoto, "Sofware Reliability Engineering: Measurement, Prediction, Application. ", Mc Graw Hill, 1987.
  12. Michael R. Lyu , "Handbook of Software Reliability Engineering. " McGraw-Hill publishing, 1995, ISBN 0-07-039400-8.
  13. Yang Gu, "Adopting ODC to improve Software Quality: A case study. " Technical report, IBM, August, 2006.
Index Terms

Computer Science
Information Sciences

Keywords

Software Reliability Stochastic Fault Fault Tolerance Phases Of Software