Abstract
Software has become an integral part of our daily routine. In the technology-driven world, reliable software are needed to maintain the pace in this modern era. Providing a reliable software in a short interval of time for fulfilling users’ requirements has become a tedious task for software developers. To resolve this issue of fast delivery of software, firms are now releasing software in multiple versions. In multi-upgradations of software, remaining bugs of the previous release are treated along with the bugs of the new release. During the software development process, firm changes the testing strategy resulting in a change in fault detection rate. The clock time at which the failure detection rate changes is known as change-point in software reliability literature. A large number of SRGMs are presented and evaluated considering various characteristics of software during the last 30 years of hiatus. Almost all SRGMs have been used extensively in the literature for reliability estimation, evaluation, and appraisal of the reliability growth of software. To the best of our knowledge, the concept of change-point has been widely discussed with respect to fault detection/removal process of single release software only. In the proposed work, we extend the idea of change-point from single release to multi-release by proposing a generalized modeling framework. Furthermore, we have used generalized modified Weibull distribution for the defect assessment. Numerical example consisting various criteria for goodness of fit, viz., MSE, Bias, Variance, and RMSPE, and coefficient of determination are included to clarify the degree of agreement of the presented model based on a real and experimental set of failure data for multiple releases.
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References
Huang CY (2005) Performance analysis of software reliability growth models with testing-effort and change-point. J Syst Softw 76(2):181–194
Huang CY, Lin CT (2010) Analysis of software reliability modeling considering testing compression factor and failure-to-fault relationship. IEEE Trans Comput 59(2):283–288
Pham H (2006) System software reliability. Springer, London
Musa JD, Iannino A, Okumoto K (1987) Software reliability, measurement, prediction and application. McGraw-Hill, New York
Kapur PK, Pham H, Gupta A, Jha PC (2011) Software reliability assessment with OR applications. Springer, London
Kapur PK, Pham H, Anand S, Yadav K (2011) A unified approach for developing reliability growth models in the presence of imperfect debugging and error generation. IEEE Trans Reliab 60(1):331–340
Zhao M (1993) Change-point problems in software and reliability. Commun Stat Theory Methods 22(3):757–768
Kapur PK, Gupta A, Shatnawi O, Yadavalli VSS (2006) Testing effort control using flexible software reliability growth model with change point. Int J Performability Eng 2(3):245–263
Kapur PK, Kumar A, Yadav K, Khatri SK (2007) Software reliability growth modelling for error of different severity using change point. Int J Qual Reliab Saf Eng 14(4):311–326
Kapur PK, Singh VB, Anand S (2007) Software reliability growth model of fielded software based on multiple change point concept using a power function of testing time. In: Quality reliability and Infocom Technology. MacMillan India Ltd, New Delhi, pp 171–178
Kapur PK, Singh VB, Anand S, Yadavalli VSS (2008) Software reliability growth model with change point and effort control using a power function of the testing time. Int J Prod Res 46(3):771–787
Zhao J, Liu H, Cui G, Yang X (2006) Software reliability growth model with change point and environmental function. J Syst Softw 79(11):1578–1587
Singh O, Garmabaki AHS, Kapur PK (2011) Unified framework for developing two dimensional software reliability growth models with change points. In: IEEE International Conference on Quality and Reliability (ICQR), held during 14–17 Sep 2011, Bangkok, pp. 570–574
Hayashida S, Inoue S, Yamada S (2014) Software reliability assessment using exponential type change point hazard rate models. Int J Reliab Qual Saf Eng 21(4). doi:10.1142/S0218539314500193
Inoue S, Hayashida S, Yamada S (2013) Extended hazard rate models for software reliability assessment with effect at change point. Int J Reliab Qual Saf Eng 20(2). doi:10.1142/S0218539313500095
Inoue S, Taniguchi S, Yamada S (2015) An all-stage truncated multiple change point model for software reliability assessment. Int J Reliab Qual Saf Eng 22(4). doi:10.1142/S0218539315500175
Inoue S, Yamada S (2010) Change point modeling for software reliability assessment depending on two-types of reliability growth factors. Ind Eng Eng Manag:616–620. doi:10.1109/IEEM.2010.5674522
Inoue S, Yamada S (2008) Optimal software release policy with change-point. In: Proceedings of 2008 IEEE international conference on industrial engineering and engineering management, pp 531–535
Chiu K-C (2015) An exploration on debugging performance for software reliability growth models with learning effects and change-points. J Ind Prod Eng 32(6):369–386
Zhao M (2003) Statistical reliability change point estimation models. In: Handbook of reliability engineering. Springer, London/New York, pp 157–163
Singh O, Singh VB, Kumar Jyotish J, Kapur PK (2009) Generalized framework for fault detection – correction process incorporating change-point. Commun Depend Qual Manag Int J 12(1):35–46
Kapur PK, Kumar J, Kumar R (2008) A unified modeling framework incorporating change-point for measuring reliability growth during software testing. OPSEARCH, Oper Res Soc India J 45(4):317–334
Chang YP (2001) Estimation of parameters for non homogeneous poisson process software reliability with change point model. Commun Stat Simul Comput 30(3):623–635
Kapur PK, Tandon A, Kaur G (2010) Multi up-gradation software reliability model, 2nd international conference on reliability, safety and hazard, held during 14–16 Dec. 2010,(ICRESH-2010), Mumbai, pp 468–474
Kapur PK, Garmabaki AHS, Singh J (2010) Multi up-gradation software reliability model with imperfect debugging. Int J Syst Assur Eng Manag 1(4):299–306
Singh O, Kapur PK, Shrivastava AK, Das L (2014) A unified approach for successive release of a software under two types of imperfect debugging. In: IEEE Xplore conference Proceedings of 3rd International Conference on Reliability, Infocom Technologies and Optimization held during October 8–10, 2014 at Amity University, Noida, Uttar Pradesh, pp. 275–280
Kapur PK, Singh O, Shrivastava AK, Singh JNP (2015) A software up-gradation model with testing effort and two types of imperfect debugging. IEEE Xplore proceedings of International conference on Futuristic Trends in Computational Analysis and Knowledge Management, pp 613–618
Kapur PK, Pham H, Aggarwal AG, Kaur G (2012) Two dimensional multi-release software reliability modeling and optimal release planning. IEEE Trans Reliab 61(3):758–768
Carrasco JMF, Ortega EMM, Corderio GM (2008) A generalized modified Weibull distribution for lifetime modeling. Comput Stat Data Anal, Elsevier 53:450–462. doi:10.1016/j.csda.2008.08.023
Mudholkar GS, Srivastava DK, Kollia GD (1996) A generalization of the Weibull distribution with application to the analysis of survival data. J Am Stat Assoc 91:1575–1583
Lai CD, Xie M, Murthy DNP (2003) A modified Weibull distribution. IEEE Trans Reliab 52:33–37
Gupta RD, Kundu D (1999) Generalized exponential distributions. Aust N Z J Stat 41:173–188
Kundu D, Rakab MZ (2005) Generalized Rayleigh distribution: different methods of estimation. Compu Stat Data Anal 49:187–200
Wood (1996) Predicting software reliability. IEEE Comput 9:69–77
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Mishra, G., Kapur, P.K., Shrivastava, A.K. (2018). A General Framework for Modeling of Multiple-Version Software with Change-Point. In: Kapur, P., Kumar, U., Verma, A. (eds) Quality, IT and Business Operations. Springer Proceedings in Business and Economics. Springer, Singapore. https://doi.org/10.1007/978-981-10-5577-5_2
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