Generic placeholder image

Recent Advances in Computer Science and Communications

Editor-in-Chief

ISSN (Print): 2666-2558
ISSN (Online): 2666-2566

General Review Article

Key Issues in Software Reliability Growth Models

Author(s): Md. Asraful Haque* and Nesar Ahmad

Volume 15, Issue 5, 2022

Published on: 12 October, 2020

Article ID: e060422186806 Pages: 7

DOI: 10.2174/2666255813999201012182821

Price: $65

Abstract

Background: Software Reliability Growth Models (SRGMs) are the most widely used mathematical models to monitor, predict and assess the software reliability. They play an important role in industries to estimate the release time of a software product. Since 1970s, researchers have suggested a large number of SRGMs to forecast software reliability based on certain assumptions. They all have explained how the system reliability changes over time by analyzing failure data set throughout the testing process. However, none of the models is universally accepted and can be used for all kinds of software.

Objectives: The objective of this paper is to highlight the limitations of SRGMs and to suggest a novel approach towards improvement.

Methods: We have presented the mathematical basis, parameters and assumptions of the software reliability model and analyzed five popular models, namely Jelinski-Moranda (J-M) model, Goel Okumoto NHPP model, Musa-Okumoto Log Poisson model, Gompertz Model and Enhanced NHPP model.

Conclusion: The paper focuses on challenges like flexibility issues, assumptions, and uncertainty factors of using SRGMs. It emphasizes considering all affecting factors in reliability calculation. A possible approach has been mentioned at the end of the paper.

Keywords: SRGMs, NHPP model, software reliability, software quality, testing, software engineering.

Graphical Abstract

[1]
P. Cao, G. Tang, Y. Zhang, and Y. Luo, Qualitative Evaluation of Software Reliability Considering Many Uncertain Factors.Ecosys-tem Assessment and Fuzzy Systems Management, Advances in Intelligent Systems and Computing. S. Q. Cao, H. Cao, (Eds). Springer, Vol. 254, 2014, pp. 199-205.
[http://dx.doi.org/10.1007/978-3-319-03449-2_20]
[2]
M. R. Lyu, "Software reliability engineering:", In: A roadmap Future of Software Engineering, Minneapolis,, 2007, pp. 153-170.
[3]
K.M.S. Faqih, "What is hampering the performance of software reliability models? A literature review", Proceedings of the Interna-tional MultiConference of Engineers and Computer Scientists, vol. 1, pp. 18-20, 2009.
[4]
C. Wohlin, M. Host, P. Runeson, and A. Wesslen, "“Software Reliability”. Encyclopedia of Physical Sciences and Technology", In: 3rd ed Academic Press, vol. 15. 2001, pp. 1-28.
[5]
J.D. Musa, A. Iannino, and K. Okumoto, Software reliability: measurement, prediction, application., McGraw-Hill, Inc.: USA, 1987.
[6]
M. Anjum, M.A. Haque, and N. Ahmad, "Analysis and ranking of software reliability models based on weighted criteria value", Int. J. Info. Technol. Comput. Sci., vol. 5, no. 2, pp. 1-14, 2013.
[http://dx.doi.org/10.5815/ijitcs.2013.02.01]
[7]
C. Wohlin, "Estimation of software reliability growth model parameters", In: Proceedings of Workshop on Reliability Analysis of System Failure Data, Microsoft Research Cambridge, UK, 2007.
[8]
L.I. Al Turk, and E.G. Alsolami, "Jelinski-Moranda software reliability growth model: A brief literature and modification", Int. J. Softw. Eng. Appl., vol. 7, no. 2, pp. 33-44, 2016.
[9]
K. Honda, H. Washizaki, and Y. Fukazawa, "Generalized software reliability model considering uncertainty and dynamics: Model and applications", Int. J. Softw. Eng. Knowl. Eng., vol. 27, no. 6, pp. 967-993, 2017.
[http://dx.doi.org/10.1142/S021819401750036X]
[10]
A.L. Goel, "Software reliability models: Assumptions, limitations, and applicability", IEEE Trans. Softw. Eng., vol. SE-11, no. 12, pp. 1411-1423, 1985.
[http://dx.doi.org/10.1109/TSE.1985.232177]
[11]
K. Song, I. Chang, and H. Pham, "A software reliability model with a weibull fault detection rate function subject to operating environ-ments", Appl. Sci. , vol. 7, no. 10, p. 983, 2017.
[http://dx.doi.org/10.3390/app7100983]
[12]
D.D. Hanagal, and N.N. Bhalerao, "Analysis of delayed s-shaped software reliability growth model with time dependent fault content rate function", J. Data Sci., vol. 16, no. 4, pp. 857-878, 2018.
[13]
P.K. Kapur, H. Pham, S. Anand, and K. Yadav, "A unified approach for developing software reliability growth models in the presence of imperfect debugging and error generation", IEEE Trans. Reliab., vol. 60, no. 1, pp. 331-340, 2011.
[http://dx.doi.org/10.1109/TR.2010.2103590]
[14]
S. Yamada, "Recent developments in software reliability modeling and its applications", In: Stochastic Reliability and Maintenance Modeling. Springer, London,, 2013, pp. 251-284.
[http://dx.doi.org/10.1007/978-1-4471-4971-2_12]
[15]
A. Birolini, Reliability Engineering: Theory and Practice., 7th ed Springer Berlin Heidelberg, 2014.
[http://dx.doi.org/10.1007/978-3-642-39535-2]
[16]
K. Sharma, R. Garg, C.K. Nagpal, and R.K. Garg, "Selection of optimal software reliability growth models using a distance based ap-proach", IEEE Trans. Reliab., vol. 59, no. 2, pp. 266-276, 2010.
[http://dx.doi.org/10.1109/TR.2010.2048657]
[17]
A.L. Goel, and K. Okumoto, "Time-dependent error-detection rate model for software reliability and other performance measures", IEEE Trans. Reliab., vol. R-28, no. 3, pp. 206-211, 1979.
[http://dx.doi.org/10.1109/TR.1979.5220566]
[18]
J.D. Musa, and K. Okumoto, "A logarithmic poisson execution time model for software reliability measurement", In: Proceedings of the 7th International Conference On Software Engineering, 1984, pp. 230-238.
[19]
"ReliaSoft Publishing Software reliability growth modeling using the standard and modified gompertz models", Reliability HotWire, Vol. 84, 2008.https://www.weibull.com/hotwire/issue84/relbasics84.htm
[20]
K. Ohishi, H. Okamura, and T. Dohi, "Gompertz software reliability model: Estimation algorithm and empirical validation", J. Syst. Softw., vol. 82, no. 3, pp. 535-543, 2009.
[http://dx.doi.org/10.1016/j.jss.2008.11.840]
[21]
S.S. Gokhale, T. Philip, P.N. Marinos, and K.S. Trivedi, "Unification of finite failure non-homogeneous Poisson process models through test coverage", In: Proceedings of 7th Int. Symposium on Software Reliability Engineering White Plains, NY, USA, 1996, pp. 299-307.
[http://dx.doi.org/10.1109/ISSRE.1996.558886]
[22]
H.C. Kim, and H.K. Park, The comparative study for ENHPP software reliability growth model based on mixture coverage function.Grid and Distributed Computing. Communications in Computer and Information Science. Springer Berlin, Heidelberg, vol. 261. 2011.
[http://dx.doi.org/10.1007/978-3-642-27180-9_23]
[23]
X. Zhang, and H. Pham, "An analysis of factors affecting software reliability", J. Syst. Softw., vol. 50, no. 1, pp. 43-56, 2000.
[http://dx.doi.org/10.1016/S0164-1212(99)00075-8]
[24]
I. Lakshmanan, and S. Ramasamy, "An artificial neural-network approach to software reliability growth modeling", Procedia Comput. Sci., vol. 57, pp. 695-702, 2015.
[http://dx.doi.org/10.1016/j.procs.2015.07.450]
[25]
C. Stringfellow, and A.A. Andrews, "An empirical method for selecting software reliability growth models", Empir. Softw. Eng., vol. 7, no. 4, pp. 319-343, 2002.
[http://dx.doi.org/10.1023/A:1020515105175]
[26]
A. Wood, "Software reliability growth models", Tandem Technical Report -96, p. 1, 1996.
[27]
M. Xie, and B. Yang, "A study of the effect of imperfect debugging on software development cost", IEEE Trans. Softw. Eng., vol. 29, no. 5, pp. 471-473, 2003.
[http://dx.doi.org/10.1109/TSE.2003.1199075]
[28]
V. Almering, M.V. Genuchten, G. Cloudt, and P.J. Sonnemans, "Using software reliability growth models in practice", IEEE Softw., vol. 24, no. 6, pp. 82-88, 2007.
[http://dx.doi.org/10.1109/MS.2007.182]
[29]
M. Zhu, and H. Pham, "A software reliability model with time-dependent fault detection and fault removal", Vietnam J. Comput. Sci., vol. 3, pp. 71-79, 2016.
[30]
N. Ahmad, M.U. Bokhari, S.M. Quadri, and M.G. Khan, "The exponentiated weibull software reliability growth model with various testing-efforts and optimal release policy: A performance analysis", Int. J. Qual. Reliab. Manage., vol. 25, no. 2, pp. 211-235, 2008.
[http://dx.doi.org/10.1108/02656710810846952]
[31]
V. Pradhan, J. Dhar, A. Kumar, and A. Bhargava, An S-shaped fault detection and correction SRGM subject to gamma-distributed ran-dom field environment and release time optimization.Asset Analytics., Springer: Singapore, 2020, pp. 285-300.
[32]
C.J. Hsu, C.Y. Huang, and J.R. Chang, "Enhancing software reliability modeling and prediction through the introduction of time-variable fault reduction factor", Appl. Math. Model., vol. 35, no. 1, pp. 506-521, 2011.
[http://dx.doi.org/10.1016/j.apm.2010.07.017]
[33]
F. Li, and Z. Yi, "A new software reliability growth model: Multigeneration faults and a power-law testing-effort function", In: Math. Probl. Eng., 2016, pp. 1-13.
[34]
H. Pham, "A new software reliability model with Vtub-shaped fault-detection rate and the uncertainty of operating environments", Optimization, vol. 63, no. 10, pp. 1481-1490, 2014.
[http://dx.doi.org/10.1080/02331934.2013.854787]
[35]
H. Pham, "A generalized fault-detection software reliability model subject to random operating environments", Vietnam J. Comput. Sci., vol. 3, no. 3, pp. 145-150, 2016.

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy