An Analysis of Software Testing Security using Quality Assurance and Reliability

  IJCOT-book-cover
 
International Journal of Computer & Organization Trends  (IJCOT)          
 
© 2017 by IJCOT Journal
Volume - 7 Issue - 6
Year of Publication : 2017
Authors :  Dr.S.Kannan, Mr.T.Pushparaj
DOI : 10.14445/22492593/IJCOT-V7I6P301

Citation

Dr.S.Kannan, Mr.T.Pushparaj "An Analysis of Software Testing Security using Quality Assurance and Reliability", International Journal of Computer & organization Trends (IJCOT), V7(6):1-10 November - December  2017, ISSN:2249-2593, www.ijcotjournal.org. Published by Seventh Sense Research Group.

Abstract

In our lives are directed by great, compositesystems with progressively complex software, and the security, security, and dependability of these systems has established a central concern. As the software in today’s arrangementsproduceslarger, it has extrafaults, and these faults adversely disturb the safety, security, and dependability of the systems. Software engineering is the submission of a methodical, disciplined, measurablemethod to the development, operation, and maintenance of software. Software divides into two pieces: internal and external quality characteristics. External quality characteristics are those portions of aproduct that face its users, where internal quality characteristics are those that do not. Quality is conformance to product requirements and should be free. This research concerns the role of software Quality. Software dependability is asignificantsurface of software quality. It is the probability of failure-free process of a computer program in a quantifiedenvironment for a quantified time. In software reliability modeling, the parameters of the model are typically assessed from the test data of the conformingconstituent. However, the widely used point estimators are subject to random differences in the data, resulting in uncertainties in these projected parameters. This research defines a new method to the problem of software testing. The method is based on Bayesian graphical models andofferingsofficial mechanisms for the logical structuring of the software testing problem, the probabilistic and arithmeticalaction of the suspicions to be addressed, the test design and analysis procedure, and the combination and suggestionof test results. Once built, the models produced are dynamic depictions of the software testingproblem. It explains essential of the mutual test-and-fixsoftware quality approach is no longer acceptable, andcharacterizes the possessions of the quality approach.

References

[1] G.L. Eyink and S. Kim, ?A Maximum Entropy Method for ParticleFiltering, J. Statistical Physics, vol. 123, no. 5, pp. 1071-1128, 2005.
[2] A.L. Goel and K. Okumoto, ?Time Dependent Error- Detection Rate Model for Software Reliability and Other Performance Measures, IEEE Trans. Reliability, vol. 28, pp. 206-211, 1979.
[3] K. Naresh Kumar, K. Krishna Reddy, Trace back of DDoS Attacks, – Volume 7 Number 1 – Apr 2014.
[4] F.E. Norman & S.L. Pfleeger, Software Metrics: ARigorousand Practical Approach, Second Edition. Boston: PWS Publishing,1997.
[5] K. Khosravi, & Y.G. Gueheneuc, ? A quality model for design patterns,2004.
[6] M. Goldstein, ?Subjective Bayesian Analysis: Principles and Practice, Bayesian Analysis, vol. 1, no. 3, pp. 403- 420, 2006.
[7] Neha Mudgal, Virtual Reality in Cognitive Rehabilitation, Volume 34 Number2– August 2016.
[8] D.E. Holmes, ?Toward a Generalized Bayesian Network, Proc. Am. Inst. Physics Conf.—Bayesian Inference and Maximum Entropy Methods in Science and Eng., vol. 872, pp. 195-202, 2006.
[9] M. Ortega, M. Perez, & T. Rojas, ?Construction of systemic quality model for evaluating a software product, Software QualityJournal 11: 219-242, 2003.
[10] E.T. Jaynes, ?Information Theory and Statistical Mechanics, Statistical Physics, pp. 181-218, 1963.
[11] C.Y. Tseng, ?Entropic Criterion for Model Selection, Physica A: Statistical and Theoretical Physics, vol. 370, no. 2, pp. 530-538, 2005.
[12] K.S. Trivedi, Probability and Statistics with Reliability, Queuing, and Computer Applications. Prentice-Hall, 1982.
[13] Dr. R. Satya Prasad ,Shaheen , G. Krishna Mohan, Two Step Approach For Software Reliability: HLSRGM, volume 4 Issue 10–Oct 2013.
[14] IEEE. ?IEEE standard for a software quality Metrics Methodology, 1993. [August 20, 2005].
[15] M. Xie, Y.S. Dai, and K.L. Poh, Computing System Reliability: Models and Analysis. Kluwer Academic, 2004.
[16] Liao H,Enke D., and Wiebe H.,An Expert Advisory Systems for ISO 9001 Quality System,Expert Systems with Applications,Vol 27,pp.313-322,2004.
[17] J. Musa, A. Iannino, and K. Okumoto, Software engineering and managing software with reliability measures. : McGraw- Hill, 1987.
[18] C.-Y. Huang and C.-T. Lin, ?Software reliability analysis by considering fault dependency and debugging time lag, IEEE Trans.Reliability, vol. 53, no. 3, pp. 436–45 0, 2006.
[19] Mfon-Abasi Raphael Idio, Measuring Sustainability Impact of Software, volume 16 number 1 – Oct 2014.
[20] P. Moranda and Z. Jelinski, Final Report on Software Reliability Study McDonnall Douglas Astronautics Company, 1972, Tech. Rep..[5] J. Musa, ?A theory of software reliability and its application, IEEETrans. Software Engineering, pp. 312–327, 1975.
[21] N. Karunanithi, D. Whitley, and Y. K. Malaiya, ?Prediction of software reliability using connectionist models, IEEE Trans.Software Engineering, vol. 18, no. 7, pp. 563–574, July 1992.
[22] G. A. Souza and S. R. Vergilio, ?Modeling software reliability growth with artificial neural networks, in IEEE Latin American TestWorkshop, Buenos Aires, Argentina, March 2006, pp. 165–170.
[23] WasimAkram Shaik1 , Rajesh Pasupuleti, Avoiding Cross Site Request Forgery (CSRF) Attack Using TwoFish Security Approach, – volume 25 Number 2 – July 2015.
[24] E. O. Costa, S. R. Vergilio, A. Pozo, and G. A. Souza, ?software reliability growth with genetic programming,? in XVIInternational Symposium of Software Reliability Engineering, USA, November 2005, IEEE Computer Society.
[25] G. Paris, D. Robiliard, and C. Fonlupt, ?Applying boosting techniques to genetic programming, in IEEE International Joint Conference on Neural Networks, 2004, pp. 1163–1168.
[26] D. Solomatine and D. Shrestha, ?Adaboost-rt: A boosting algorithm for regression problems, Intelligent Artificial Evolution, pp. 312– 326, 2001.
[27] Rodriguez-Dapena, ?Software Safety Certification: A Multinational Problem, IEEE Software, July/August 1999, p. 31, © 1999 IEEE.
[28] G. Gordon Schulmeyer ?Handbook of Software Quality Assurance, Fourth Edition, ARTECH HOUSE, INC. 2008, pp. 212-213.
[29] The NASA Software Assurance Standard, NASA-STD- 8739.8.
[30] Garvin A., ?Competing on the Eight dimensions of Quality Havard Business Review Nov-Dec 101–109, 1987.

Keywords
It explains essential of the mutual test-and-fixsoftware quality approach is no longer acceptable, andcharacterizes the possessions of the quality approach.