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Reseach Article

Software Reliability Testing using Monte Carlo Methods

by Harnam Singh, Preet Pal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 69 - Number 4
Year of Publication: 2013
Authors: Harnam Singh, Preet Pal
10.5120/11834-7554

Harnam Singh, Preet Pal . Software Reliability Testing using Monte Carlo Methods. International Journal of Computer Applications. 69, 4 ( May 2013), 41-44. DOI=10.5120/11834-7554

@article{ 10.5120/11834-7554,
author = { Harnam Singh, Preet Pal },
title = { Software Reliability Testing using Monte Carlo Methods },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 69 },
number = { 4 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 41-44 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume69/number4/11834-7554/ },
doi = { 10.5120/11834-7554 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:29:22.865058+05:30
%A Harnam Singh
%A Preet Pal
%T Software Reliability Testing using Monte Carlo Methods
%J International Journal of Computer Applications
%@ 0975-8887
%V 69
%N 4
%P 41-44
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Monte Carlo method is used in this paper to test the software reliability. The Monte Carlo method is a technique that can be used to solve mathematical or statistical problems. Monte Carlo simulation uses frequent sampling to determine the properties of some phenomenon. There have been very rare uses of such simulation methods for software testing. This paper provides an accurate algorithm for testing software based on Monte Carlo Methods. The results would decide the percentage reliability of the software. This scheme has a number of applications in financial analysis, Econometric, statistics, software testing, fault detection in circuits and many more.

References
  1. Paul Coddington. "Monte Carlo Simulation for Statistical Physics. " Northeast Parallel Architectures Center at Syracuse University
  2. Brain Korver 1994 "The Monte Carlo Method for Software Reliability Theory", TR 94-1
  3. Bo Zhou, Hiroyuki Okamura and Tadashi Dohi "Markov Chain Monte Carlo Random Testing"Software Reliability. Hoang Pham.
  4. John D. Musa. Software reliability engineering: more reliable software faster and cheaper. McGraw-Hill. ISBN 0-07-060319-7
  5. Bo Zhou, Hiroyuki Okamura, and Tadashi Dohi(2010) "Markov Chain Monte Carlo Random Testing" T. H. Kim and H. Adeli (Eds. ): AST/UCMA/ISA/ACN 2010, LNCS 6059, pp. 447–456, 2010. Springer-Verlag Berlin Heidelberg 2010
  6. Kazuhiko Hayakawa, M. Hashem Pesaran(2012) "Robust Standard Errors in Transformed Likelihood Estimation of Dynamic Panel Data Models" University of Cambridge ESRC Grant No. ES/1031626/1
  7. Zeyn A. Saigol(2008) "Monte-Carlo Testing for AUV Planning Software" University of Birmingham. .
  8. Stefan Pauli, Peter Arbenza , Christoph Schwab "Intrinsic Fault Tolerance of Multi Level Monte Carlo Methods" Journal of Parallel and Distributed Computing.
  9. A. P Lyubartsev, A. A. Martsinovski, S. V. Shevkunov, and P. N. Vorontsov-Velyaminov(1991) "New approach to Monte Carlo calculation of the free energy:Method of expanded ensembles" J. Chem. Phys. 96 (3), 1 February 1992 1992 American Institute of Physics.
  10. Nathan A. Thompson, David J. Weiss(2011) presented a system "A Framework for the Development of Computerized Adaptive Tests" Practical Assessment, Research & Evaluation ISSN 1531-7714 Volume 16, Number 1, January 2011
  11. T. B. Whitaker,J. W. Dickens(1975) "Monte Carlo Technique to simulate Aflatoxin Testing Programs for Peanuts" Journal of the American Oil Chemists Scoiety,Vol. 53,No. 8,Pages:545-547.
Index Terms

Computer Science
Information Sciences

Keywords

Monte Carlo method Software testing Document characterization