Abstract
The software industry can be considered as the typical high technology industry where rate of innovation and knowledge creation plays a pivotal role for continued firm growth. In the last few decades it has been observed that the world of software development management has evolved rapidly due to the intensified market competition. In particular the use of feature-addition model of software products in the industry is fast becoming the commonplace. The up-gradation model can be characterized by increasing the number of features in the software that will give the firm competitive edge in the market. The up-gradation of the system is done by extending it through add-ons, interfacing with other applications, etc. Continuous up-gradation of software’s also brings complexity in the systems once it failed to work properly. In recent years, there has been a growing interest to predict the link between the rates of failure and the reliability of software. Many software reliability growth models (SRGM) have been proposed over past three decades that estimate the reliability of a software system as it undergoes changes through the removal of failure causing faults. But unfortunately most of the models did not consider anything about the increase in failure rate once an up-gradation is made on the software. The objective of this paper is to propose the software reliability growth model that incorporates the effect of enhancement of features on software during testing and debugging process. In addition, we have also discussed the related optimal release time policy that minimizes the total cost.
Similar content being viewed by others
References
Jiantao P (1999) ’Software Reliability’ Carnegie Mellon University (working paper) available at:http://www.ece.cmu.edu/~koopman/des_s99/sw_reliability/
Goel AL, Okumoto K (1979) Time dependent error detection rate model for software reliability and other performance measures. IEEE Trans Reliab R-28(3):206–211
Yamada S, Ohba M, Osaki S (1983) S-shaped software reliability growth modeling for software error detection. IEEE Trans Reliab R-32(5):475–484
Kapur PK, Younes S, Agrawala S (1995) Generalized erlang software reliability growth model. ASOR Bull 14(1): 5–11
Kapur PK, Garg RB (1992) A software reliability growth model for an error removal phenomenon. Software Eng J 7:291–294
Ohba M (1984) Software reliability analysis models. IBM J Res Develop 28:428–443
Bittanti S, Bolzern P, Pedrotti E, Scattolini R (1988) A flexible modelling approach for software reliability growth. Software Reliability Modelling and Identification. (Ed) Goos G., Harmanis J. Software Reliability Modelling and Identification, Springer Verlag, Berlin 101–140
Obha M, Yamada S (1984) S-shaped software Reliability Growth Model. Proceedings of the 4th National Conference on Reliability and Maintainability, 430–436
Yamada S, Osaki S, Narihisa H (1986) Discrete models for software reliability evaluation. (Eds) Basy A.P. Reliability and quality control, London: Elsevier, STR. 401–412
Kapur PK, Garg RB, Kumar S (1999) Contributions to hardware and software reliability. Singapore: World Scientific
Garrison K (1993) Estimating defects in commercial software during operational Use. IEEE Trans Reliab 42(1): 107–115
Tamura Y, Yamada S, Kimura M (2000) Software reliability modeling in distributed development environment. J Qual Mainten Electron Commun Japan Part 3, 83(12):1–8
Musa JD, Iannino A, Okumoto K (1987) Software reliability: measurement, prediction, application. McGraw-Hill New York
Yamada S, Osaki S (1987) Optimal release policies with simultaneous cost and reliability requirements. Euro J Oper Res 31(1):46–51
Abdel AA, Chan PY, Littlewood B (1986) Evaluation of competing software reliability predictions. IEEE Trans Soft Eng 12(9):950–967
Kapur PK, Garg RB (1991) Optimal release policies for software systems with testing effort. Inter J Sys Sci 22: 1563–1571
Brooks WD, Motley RW (1980) Analysis of discrete software reliability models — Technical report RADC-TR-80-84. New York: Rome Air development center
Stalk G (1988) Time — the next source of competitive advantage. Harvard Business Rev 66:41–51
Preston GS, Donald GR (1998) Developing Products in Half the Time: New Rules, New Tools. 2nd Edition, Wiley publishing
Tadashi D, Yasuhiko N, Shunji O (1999) Optimal software release scheduling based on artificial neural networks. Ann Soft Eng 8(4):167–185
Yen-Chang C (2004) A sequential software release policy. Ann Inst Statist Math 56(1):193–204
Chin-Yu H (2005) Performance analysis of software reliability growth models with testing-effort and change-point. J Syst Software 77(2):139–155
Shinji I, Shigeru Y (2007) Generalized discrete software reliability modelling with effect of program size. IEEE Trans Syst Manag Cybernetics-Part A: Syst and Hum 37(2):170–179
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Kapur, P.K., Garg, R.B., Chanda, U. et al. Development of software reliability growth model incorporating enhancement of features and related release policy. Int J Syst Assur Eng Manag 1, 52–58 (2010). https://doi.org/10.1007/s13198-010-0008-7
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13198-010-0008-7