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Software reliability growth modeling for agile software development

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Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The frequent incremental release of software in agile development impacts the overall reliability of the product. In this paper, we propose a generic software reliability model for the agile process, taking permanent and transient faults into consideration. The proposed model is implemented using the NHPP (non-homogenous Poisson process) and the Musa model. The comparison of the two implementations yields an effective, empirical and reliable model for agile software development.
Rocznik
Strony
777--783
Opis fizyczny
Bibliogr. 28 poz., rys., tab., wykr.
Twórcy
autor
  • Department of Computer Science and Engineering, Graphic Era University, Dehradun, Uttarakhand, India
autor
  • Department of Mathematics, Graphic Era University, Dehradun, Uttarakhand, India
autor
  • Department of Mathematics, Graphic Era University, Dehradun, Uttarakhand, India; Department of Computer Science and Engineering, Graphic Era University, Dehradun, Uttarakhand, India
Bibliografia
  • [1] Aggarwal, A.G., Kapur, P. and Garmabaki, A. (2011). Imperfect debugging software reliability growth model for multiple releases, Proceedings of the 5th National Conference on Computing for Nation Development-INDIACOM, New Delhi, India, pp. 337–344.
  • [2] Agile Alliance (2017). http://www.agilealliance.org/.
  • [3] Dingsøyr, T. and Lassenius, C. (2016). Emerging themes in agile software development: Introduction to the special section on continuous value delivery, Information and Software Technology 77(1): 56–60.
  • [4] Fang, C.-C. and Yeh, C.-W. (2016). Effective confidence interval estimation of fault-detection process of software reliability growth models, International Journal of Systems Science 47(12): 2878–2892.
  • [5] Farr, W. (1996). Software reliability modeling survey, in M.R. Lyu (Eds.), Handbook of Software Reliability Engineering, McGraw-Hill, Inc. Hightstown, NJ, pp. 71–117.
  • [6] Goel, A.L. (1985). Software reliability models: Assumptions, limitations, and applicability, IEEE Transactions on Software Engineering 11(12): 1411–1423.
  • [7] Goel, A.L. and Okumoto, K. (1979). Time-dependent error-detection rate model for software reliability and other performance measures, IEEE Transactions on Reliability 28(3): 206–211.
  • [8] Goel, A.L. and Okumoto, K. (1980). A time dependent error detection rate model for software performance assessment with applications, Technical report, DTIC Document, http://www.dtic.mil/docs/citations/ADA088186.
  • [9] Goyal, N. and Ram, M. (2014). Software development life cycle testing analysis: A reliability approach, Mathematics in Engineering, Science & Aerospace 5(3): 313–329.
  • [10] Jelinski, Z. and Moranda, P. (1972). Software reliability research, in W. Freiberger (Ed.), Statistical Computer Performance Evaluation, Academic Press, New York, NY, pp. 465–484.
  • [11] Kapur, P., Sachdeva, N. and Singh, J.N. (2014). Optimal cost: A criterion to release multiple versions of software, International Journal of System Assurance Engineering and Management 5(2): 174–180.
  • [12] Kapur, P., Younes, S. and Agarwala, S. (1995). Generalised Erlang model with n types of faults, ASOR Bulletin 14(1): 5–11.
  • [13] Lai, R. and Garg, M. (2012). A detailed study of NHPP software reliability models, Journal of Software 7(6): 1296–1306.
  • [14] Matsumoto, K.I., Inoue, K., Kikuno, T. and Torii, K. (1988). Experimental evaluation of software reliability growth models, 11th International Symposium FTCS-18, Tokyo, Japan, pp. 148–153.
  • [15] Musa, J.D., Iannino, A. and Okumoto, K. (1987). Software Reliability: Measurement, Prediction, Application, McGraw-Hill, Inc., New York, NY.
  • [16] Palma, J., Tian, J. and Lu, P. (1993). Collecting data for software reliability analysis and modeling, Proceedings of the 1993 Conference of the Centre for Advanced Studies on Collaborative Research: Software Engineering, Toronto, Canada, Vol. 1, pp. 483–494.
  • [17] Pandey, A.K. and Goyal, N.K. (2015). Background: Software quality and reliability prediction, in A.K. Pandey and N.K. Goyal (Eds.), Early Software Reliability Prediction, Studies in Fuzziness and Soft Computing, Vol. 303, Springer, New Delhi, pp. 17–33.
  • [18] Pham, H. and Zhang, X. (2003). NHPP software reliability and cost models with testing coverage, European Journal of Operational Research 145(2): 443–454.
  • [19] Pham, L. and Pham, H. (2000). Software reliability models with time-dependent hazard function based on Bayesian approach, IEEE Transactions on Systems, Man, and Cybernetics A: Systems and Humans 30(1): 25–35.
  • [20] Rawat, S., Rawat, R.S. and Ram, M. (2015). A review on software reliability: Metrics, models and tools, Mathematics in Engineering, Science & Aerospace 6(2): 135–156.
  • [21] Singh, O., Anand, A., Aggrawal, D. and Singh, J. (2014). Modeling multi up-gradations of software with fault severity and measuring reliability for each release, International Journal of System Assurance Engineering and Management 5(2): 195–203.
  • [22] Singh, V., Kapur, P. and Mashaallh, B. (2008). Considering errors of different severity in software reliability growth modeling using fault dependency and various debugging time lag functions, in A.K. Verma et al. (Eds.), Proceedings of Advances in Performance and Safety of Complex Systems, MacMillan India, New Delhi, pp. 839–849.
  • [23] Sommerville, I. (2011). Software Engineering, Addison-Wesley, Boston, MA.
  • [24] West, D., Grant, T., Gerush, M. and Dsilva, D. (2010). Agile development: Mainstream adoption has changed agility, Forrester Research 2(1): 41.
  • [25] Wilson, T. (1997). Software failure: Management failure. Amazing stories and cautionary tales, International Journal of Information Management 17(5): 387.
  • [26] Yamada, S. (1994). Optimal release problems with warranty period based on a software maintenance cost model, Transactions of the Information Processing Society of Japan 35(9): 2197–2202.
  • [27] Yamada, S., Ohba, M. and Osaki, S. (1983). S-shaped reliability growth modeling for software error detection, IEEE Transactions on Reliability 32(5): 475–484.
  • [28] Yamada, S., Ohba, M. and Osaki, S. (1984). S-shaped software reliability growth models and their applications, IEEE Transactions on Reliability 33(4): 289–292.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-431f4d85-dadb-477b-b126-181386653069
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