International Journal of Information Technology and Computer Science (IJITCS)
IJITCS Vol. 10, No. 5, 8 May 2018
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Design of Generalized Weighted Laplacian Based Quality Assessment for Software Reliability Growth Models
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Author(s)
Chandra MouliVenkata Srinivas Akana
1,*
C. Divakar
2
Ch. Satyanarayana
3
Index Terms
Quality Assessment, Software Reliability Growth Models, residual fault, fault detection rate and NHPP
Abstract
The reliability of a software depends on the quality. So, the software growth models require efficient quality assessment procedure. It can be estimated by various parameters. The current paper proposes a novel approach for assessment of quality based on the Generalized Weighted Laplacian (GWL) method. The proposed method evaluates various parameters for detection and removal time. The Mean Value Function (MVF) is then calculated and the quality of the software is estimated, based on the detection of failures. The proposed method is evaluated on process CMMI level 5 project data and the experimental results shows the efficiency of the proposed method.
Cite This Paper
Chandra MouliVenkata Srinivas Akana, C. Divakar, Ch. Satyanarayana, "Design of Generalized Weighted Laplacian Based Quality Assessment for Software Reliability Growth Models", International Journal of Information Technology and Computer Science(IJITCS), Vol.10, No.5, pp.48-54, 2018. DOI:10.5815/ijitcs.2018.05.05
Reference
[1]Kan Stephen H., “Metrics. and Models. in Software Quality, Engineering”, Addison Wesley Longman Publishing, Boston MA, USA, 2002, ISBN:0201729156.
[2]ChinYu Huang,Kuo Sy-Yen,Michael Lyu, “An Assessment of Testing, Effort Dependent, SRGMs,” IEEE Transactions on Reliability, Volume: 56, Issue: 2, June 2007, Pages: 198–211, DOI: 10.1109/TR.2007.895301
[3]Deissenboeck Florian, Juergens Elmar, Lochmann Klaus, WagnerStefan, “Software, quality, models: Purposes, requirements & usage scenarios”, WOSQ‘09. ICSE Workshop,2009, Print ISBN: 978-1-4244-3723-8, DOI: 10.1109/WOSQ.2009.5071551
[4]Chin Yu Huang, “Performance analysis of SRGMS with testing-effort, and change-point”, Journal of Systems and Software, Volume76, Issue 2, (May 2005), Pages 181-194,DOI:http://dx.doi.org/10.1016/j.jss.2004.04.024.
[5]Shyur, H. J., “A stochastic software reliability model with imperfect-debugging and change-point”, Journal of Systems and Software, Volume 66, Issue 2, May 2003, Page(s): 135-141, DOI: 10.1016/S0164-1212(02)00071-7
[6]Kapur P. K.,Pham H.,Anand Sameer,Yadav Kalpana, “A Unified, Approach, for Developing, SRGMSs. in the Presence of, Imperfect, Debugging and Error, Generation,” IEEE, Transactions, on Reliability, Volume: 60, Issue 1, March 2011, Page(s): 331–340, DOI: 10.1109/TR.2010.2103590
[7]Bokhari M.U. and Ahmad N., “Analysis of a SoftwareReliability Growth Model: The Case of Log, Logistic Test Effort Function,” MS'06 Proceedings of the 17th IASTED international conference on Modeling and simulation, 2006, Pages 540-545,ISBN:0-88986-592-2, DOI: http://dl.acm.org/citation.cfm?id=1167209
[8]ShigeruYamada, “Software Reliability Modeling: Fundamentals, and Applications,” (Print)ISBN:978-4-431-54564-4,(Online)978-4-431-54565-1.
[9]Kapur P.K., Pham Hoang A., Gupta, Jha P.C., “Software Reliability, Assessment, with, OR Applications,” ISBN: 978-0-85729-203-2 (Print) 978-0-85729-204-9 (Online)
[10]Stefan Lessmann, Swantje Pietsch, Baesens Bart, Mues Christophe, “Benchmarking, Classification Models, for Software, Defect Prediction- A Proposed. Framework, and Novel Findings”, IEEE Transactions on Software Engineering, Volume 34, Issue 4, July to Aug 2008, Page(s): 485 – 496, DOI: 10.1109/TSE.2008.35
[11]N. Ahmad, Khan M.G.M., L.S. Rafi, "A study ,of ,testing effort ,dependent inflection Sâshaped SRGMs with, imperfect, debugging", International Journal of Quality and Reliability, Management, 2010, Volume27, Issue 1, pages: 89–110, DOI: https://doi.org/10.1108/02656711011009335
[12]Liebchen Gernot A, Shepperd Martin, “Data sets and Data Quality in Software Engineering”, PROMISE '08Proceeding of the fourth international workshop on Predictor models, in software engg. (PROMISE'08), 2008, ACM, New York, USA, pages: 39-44,DOI:http://dx.doi.org/10.1145/1370788.137079
[13]Afzal Wasif and Torkar Richard, “Review - On the application, of genetic, Programming, for software, engineering predictive modeling”, Expert Syst. Appl. 38, 9 (Sept 2011), 11984 to 11997, DOI=http://dx.doi.org/10.1016/j.eswa.2011.03.041.
[14]Samoladas Ioannis , Gousios Georgios , Spinellis Diomidis , Stamelos Ioannis , “The SQO-OSS Quality Model: Measurement Based Open source Software Evaluation,” Vol. 275,IFIP series: The International, Federation for, Information Processing, pp 237-248.
[15]Sharma Kapil,Garg Rakesh , Nagpal C.K.,Garg R.K., “Selection of Optimal SRGMs Using a Distance. Based Approach,” IEEE Transactions on Reliability(Volume: 59, Issue:2, June 2010 ), Page(s): 266 – 276.
[16]Ohishi Koji, Okamura Hiroyuki, and Dohi Tadashi. 2009. Gompertz software reliability model: Estimation, algorithm and empirical, validation, J. Syst. Softw. 82, March 2009, 535-543. DOI=http://dx.doi.org/10.1016/j.jss.2008.11.840.
[17]Huang Chin Yu,Lyu Michael R., “Estimation & Analysis of Some Generalized Multiple, Change, Point Software Reliability Models,” IEEE Transactions on Reliability ( Volume: 60, Issue: 2, June 2011), Page(s): 498 – 514.
[18]Huang Chin Yu, Hung Tsui-Ying, “Software, reliability, analysis and assessment using queuing. models with multiple. change points”, Vol. 60, Issue 7, October 2010, Pages 2015–2030.
[19]Li X., Xie M., Ng S.H., “Sensitivity analysis of release time of software reliability models incorporating testing effort with multiple change-points”, Applied Mathematical Modeling, Volume 34, Issue 11, November 2010, Pages 3560-3570, DOI: https://doi.org/10.1016/j.apm.2010.03.006
[20]Kalaimagal Sivamuni and Srinivasan Rengaramanujam, 2008, A retrospective,. on software, component quality models, ACM SIGSOFT Engg. Notes, Volume 33, Issue 6 (October 2008), Pages 1 to 10,DOI:http://dx.doi.org/10.1145/1449603.1449611.
[21]Saied A. Keshtgar, Bahman B Araseh , “ Enhancing software reliability against soft error using minimum redundancy on critical data “, I.J.Computer Network and Information Security, 2017, 5, 21-30, May 2017, in MECS (http://www.mecspress.org/), DOI: 10.5815/ijcnis.2017.05.03
[22]Mohd. Anjum, Md. Asraful Haque, Nesar Ahmad, “Analysis and Ranking of Software Reliability Models Based on Weighted Criteria Value”, I.J. Information Technology and Computer Science,2013, 02,1-14, January 2013 in MECS (http://www.mecspress.org/) DOI: 10.5815/ijitcs.2013.02.01
[23]Luo Yan, Bergander Torsten, Hamza Ben A., Software Reliability Growth Modeling using a Weighted Laplace Test Statistic, Computer Software and Applications Conference, 2007. COMPSAC 2007. DOI: 10.1109/COMPSAC.2007.194
[24]Krishna B. Misra, Handbook of Performability Engineering, Springer, London, 2008, Print ISBN 978-1-84800-130-5, Online ISBN 978-1-84800-131-2, DOI https://doi.org/10.1007/978-1-84800-131-2
[25]Akana Chandra Mouli Venkata Srinivas, Divakar C., Satyanarayana Ch., “Adaptive Mean Value Function Based Quality Assessment of Software Reliable Growth Models”, Computer Engineering and Intelligent Systems, IISTE, Volume 5, Issue 3, (March 2014), Page(s): 43-49, ISSN 2222-1719 (Paper) ISSN 2222-2863 (Online), DOI: http://www.iiste.org/Journals/index.php/CEIS/article/view/11689/12033
[26]Akana Chandra Mouli Venkata Srinivas, Divakar C., Satyanarayana Ch., “Residual Fault Detection and Performance Analysis of G-O Software Growth Model”, Journal of Current Computer Science and Technology, Volume 5, Issue 3, March 2015, pages(s): 5-7, DOI: http://innovativejournal.in/index.php/ajcem/article/viewFile/44/37
[27]Lyu M.R., Kuo Sy-Yen, Huang Chin-Yu, "Effort-index-based software reliability growth models and performance assessment", Proceedings 24th Annual International Computer Software and Applications Conference COMPSAC2000, 2000, DOI: 10.1109/CMPSAC.2000.884764.
[28]Xie M., Hu Q. P., Wu Y. P., Ng S. H., A study of the modeling and analysis of software fault-detection and fault-correction processes, Wiley Online Library, 2006, Pages: 459–470, DOI: 10.1002/qre.827.
[29]AIAA/ANSI “Recommended Practice for Software Reliability, the American Institute of Aeronautics and Astronautics”, Washington DC, Aerospace Center, R-013, 1992,-ISBN 1-56347-024-1.