Research Article

Modified Jelinski-Moranda Software Reliability Model with Imperfect Debugging Phenomenon

by  G. S. Mahapatra, P. Roy
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 48 - Issue 18
Published: June 2012
Authors: G. S. Mahapatra, P. Roy
10.5120/7451-0534
PDF

G. S. Mahapatra, P. Roy . Modified Jelinski-Moranda Software Reliability Model with Imperfect Debugging Phenomenon. International Journal of Computer Applications. 48, 18 (June 2012), 38-46. DOI=10.5120/7451-0534

                        @article{ 10.5120/7451-0534,
                        author  = { G. S. Mahapatra,P. Roy },
                        title   = { Modified Jelinski-Moranda Software Reliability Model with Imperfect Debugging Phenomenon },
                        journal = { International Journal of Computer Applications },
                        year    = { 2012 },
                        volume  = { 48 },
                        number  = { 18 },
                        pages   = { 38-46 },
                        doi     = { 10.5120/7451-0534 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2012
                        %A G. S. Mahapatra
                        %A P. Roy
                        %T Modified Jelinski-Moranda Software Reliability Model with Imperfect Debugging Phenomenon%T 
                        %J International Journal of Computer Applications
                        %V 48
                        %N 18
                        %P 38-46
                        %R 10.5120/7451-0534
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, we have modified the Jelinski-Moranda (J-M) model of software reliability using imperfect debugging process in fault removal activity. The J-M model was developed assuming the debugging process to be perfect which implies that there is one-to-one correspondence between the number of failures observed and faults removed. But in reality, it is possible that the fault which is supposed to have been removed may cause a new failure. In the proposed modified J-M model, we consider that whenever a failure occurs, the detected fault is not perfectly removed and there is a chance of raising new fault/faults due to wrong diagnosis or incorrect modifications in the software. In this paper, we develop a modified J-M model which can describe the imperfect debugging process. The parameters of our modified J-M model are estimated by using maximum-likelihood estimation method. Applicability of the model has been shown on the failure data set of Musa.

References
  • Lyu, M. R. 1996. Handbook of Software Reliability Engineering. McGraw-Hill.
  • Musa, J. D. , Iannino, A. , and Okumoto, K. 1990. Software Reliability: Measurement, Prediction, Application. McGraw-Hill.
  • Jelinski, Z. and Moranda, P. B. 1972. Software reliability research, Statistical Computer Performance Evaluation. Academic Press: New York, 465-484.
  • Littlewood, B. 1987. How good are software reliability predictions?. Software Reliability: Achievement and Assessment. Blackwell Scientific Publications. 154-166.
  • Musa J. D. 1975. A theory of software reliability and its application. IEEE T. Software Eng. 1(3), 312-327.
  • Goel, A. L. , and Okumoto, K. 1979. Time dependent error detection rate model for software reliability and other performance measures. IEEE T. Reliab. R-28(3), 206-211.
  • Yamada, S. , Ohba, M. and Osaki, S. 1983. S-shaped reliability growth modeling for software error detection. IEEE T. Reliab. R-32(5), 475-484.
  • Ohba, M. 1984. Software reliability analysis models. IBM J. Res. Dev. 28(4), 428-443.
  • Goel, A. L. 1985. Software reliability models: assumptions, limitations and applicability. IEEE T. Software Eng. SE-11(12), 1411-1423.
  • Kapur, P. K. , and Garg, R. B. 1990. Optimal release policy for software reliability growth models under imperfect debugging. Oper. Res. RAIRO. 24(3), 295-305.
  • Chang, Y. C. , and Liu, C. T. 2009. A generalized JM model with applications to imperfect debugging in software reliability. Appl. Math. Model. 33, 3578-3588.
  • Shyur, H. J. 2003. A stochastic software reliability model with imperfect-debugging and change-point. J. Syst. Software. 66(2), 135-141.
  • Kapur, P. K. , Singh, O. M. P. , Shatnawi, O. , and Gupta, A. 2006. A discrete NHPP model for software reliability growth with imperfect fault debugging and fault generation. Int. J. Perform. Eng. 2(4), 351-368.
  • Prasad, R. S. , Raju, O. N. , and Kantam, R. R. L. 2010. SRGM with imperfect debugging by genetic algorithms. Int. J. Software Eng. Appl. 1(2), 66-79.
  • Raju, O. N. 2011. Software reliability growth models for the safety critical software with imperfect debugging. Int. J. Comput. Sci. Eng. 3(8), 3019-3026.
  • Xie, M. Dai, Y. S. and Poh, K. L. 2004. Computing System Reliability Models and Analysis. Kluwer Academic Publisher.
  • Kremer, W. 1983. Birth-death and bug counting. IEEE T. Reliab. R-32(1), 37-47.
  • Musa, J. D. 1980. Software Reliability Data. Data & Analysis Center for Software.
  • Dawid, A. P. 1984. Statistical theory: the prequential approach. J. Roy. Stat. Soc. A. 147, 278-292.
  • Pham, H. 2006. System Software Reliability. Springer.
  • Bittanti, S. 1988. Software Reliability Modelling and Identification (Lecture Notes in Computer Science). Springer-Verlag.
Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Software Reliability Jelinski-moranda Model Failure Maximum Likelihood Estimation Imperfect Debugging

Powered by PhDFocusTM