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Academic literature on the topic 'JELINSKI-MORANDA MODEL'

Author: Grafiati
Published: 11 September 2023

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Journal articles on the topic "JELINSKI-MORANDA MODEL"

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S.Mahapatra, G., and P. Roy. "Modified Jelinski-Moranda Software Reliability Model with Imperfect Debugging Phenomenon." International Journal of Computer Applications 48, no. 18 (June 30, 2012): 38–46. http://dx.doi.org/10.5120/7451-0534.

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Al Turk, Lutfiah Ismail, and Eftekhar Gabel Alsolami. "Jelinski-Moranda Software Reliablity Growth Model : A Brief Literature and Modification." International Journal of Software Engineering & Applications 7, no. 2 (March 31, 2016): 33–44. http://dx.doi.org/10.5121/ijsea.2016.7204.

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Littlewood, Bev, and Ariela Sofer. "A Bayesian modification to the Jelinski-Moranda software reliability growth model." Software Engineering Journal 2, no. 2 (1987): 30. http://dx.doi.org/10.1049/sej.1987.0005.

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Washburn, Alan. "A sequential Bayesian generalization of the Jelinski–Moranda software reliability model." Naval Research Logistics 53, no. 4 (June 2006): 354–62. http://dx.doi.org/10.1002/nav.20148.

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INOUE, SHINJI, SHIHO HAYASHIDA, and SHIGERU YAMADA. "EXTENDED HAZARD RATE MODELS FOR SOFTWARE RELIABILITY ASSESSMENT WITH EFFECT AT CHANGE-POINT." International Journal of Reliability, Quality and Safety Engineering 20, no. 02 (April 2013): 1350009. http://dx.doi.org/10.1142/s0218539313500095.

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A software hazard rate model is known as one of the important and useful mathematical models for describing the software failure occurrence phenomenon observed in a testing phase. It is difficult to say that the testing environment always constant during a testing phase due to changing the specification and fault target and so forth. Therefore, taking into consideration of the effect of the change in software reliability growth modeling is expected to conduct more accurate software reliability assessment. In this paper, we develop extended software hazard rate models based on well-known Jelinski–Moranda and Moranda models, by considering with a change of testing environment. Especially in this paper, we incorporate the uncertainty of the effect of the change on the software reliability growth process into the software hazard rate modeling. Finally, we show numerical examples for our models and results of model comparisons by using actual data.
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Barghout, May. "Predicting software reliability using an imperfect debugging Jelinski Moranda Non-homogeneous Poisson Process model." Model Assisted Statistics and Applications 5, no. 1 (February 11, 2010): 31–41. http://dx.doi.org/10.3233/mas-2010-0127.

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Jukić, Dragan. "TheLp-norm estimation of the parameters for the Jelinski–Moranda model in software reliability." International Journal of Computer Mathematics 89, no. 4 (March 2012): 467–81. http://dx.doi.org/10.1080/00207160.2011.642299.

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Van Pul, Mark. "Simulations on the Jelinski-Moranda model of software reliability; application of some parametric bootstrap methods." Statistics and Computing 2, no. 3 (September 1992): 121–36. http://dx.doi.org/10.1007/bf01891204.

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boland, Philip J., Frank proschan, and Y. L. Tong. "Fault Diversity in Software Reliability." Probability in the Engineering and Informational Sciences 1, no. 2 (April 1987): 175–87. http://dx.doi.org/10.1017/s0269964800000383.

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Diversity of bugs or faults in a software system is a factor contributing to software unreliability which has not yet been appropriately emphasized. This paper is written with the intention of demonstrating the impact of fault diversity on the time to detection of software bugs. A new discrete software reliability model based on the multinomial distribution is introduced. It is shown that for models of this type, the more diverse the fault probabilities are, the longer (stochastically) it takes to detect or eliminate any n faults, while the smaller (stochastically) will be the number of faults detected or eliminated during a given amount of time (or during a given number of inputs to the system). The impact of fault diversity is also demonstrated for the Jelinski–Moranda model.
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Al turk, Lutfiah Ismail, and Eftekhar Gabel Alsolami. "A Comparison Study of Estimation Methods for Generalized Jelinski-Moranda Model Based on Various Simulated Patterns." International Journal of Software Engineering & Applications 7, no. 3 (May 30, 2016): 27–48. http://dx.doi.org/10.5121/ijsea.2016.7303.

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Dissertations / Theses on the topic "JELINSKI-MORANDA MODEL"

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Baratela, Daniele da Silva. "Inferência Bayesiana para o Modelo de Jelinski-Moranda via Parâmetros Ortogonais." Universidade de São Paulo, 1997. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-19032018-164929/.

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Apresentamos neste trabalho, um estudo do modelo de confiabilidade de software de Jelinski e Moranda (1972). Enfocamos, a importância da análise Bayesianapara a correção da instabilidade do estimador de máxima verossimilhança de N (número de erros do software), e a ortogonalização de Cox e Reid (1987) para a realização de inferência Bayesiana sobre a taxa de falhas A. Também, caractenzamos a existência da densidade a posteriori de { quando admitimos densidades a priori não-informativas e impróprias aos parâmetros do modelo. Destacamos o comportamento dos métodos de aproximação de Monte Carlo em cadeias de Markov, para a obtenção da distribuição a posteriori de N quando esta é imprópria.
In this work is presented an analysis of the Jelinski-Moranda model (1972). Special importance are given to the instability of the maximum-likelihood estimator of // (the number of software failures) and the orthogonal parameters (Cox and Reid, 1987) to obtain a Bayesian analysis of the failure rate. Also, the existence of the posterior distribution of N when an improper prior is used is charactenzed. The behavior of the MCMC to simulate the posterior distribution of Nwith improper priors is emphasized.
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SIKARWAR, INDRAJEET SINGH. "A NEW VARIANT OF JELINSKI-MORANDA MODEL FOR SOFTWARE RELIABILITY GROWTH MODELLING." Thesis, 2015. http://dspace.dtu.ac.in:8080/jspui/handle/repository/15572.

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The software is becoming an integral part of the human life and the dependency over software is increasing exponentially with the advancement of technology. The usage of software is inevitable to many aerospace, medical, industrial, military, and even commercial systems. Hence, there is a need of reliable software system that will be operational without failure, for the specified period of time, in given environmental conditions. Reliability is one of the important aspects of the software quality. The fault exists in the software causes failure to the system and hence reduces the reliability. The proposed model is a variant of Jelinski-Moranda software reliability growth model. This model assumes that faults in the software may be dependent on each other. Whenever a software failure detected, the concerned fault is removed immediately with probability p and no new error(s) are introduced. It is further assumed that the fault removal /correction process may correct the part of remaining failures too. This model is more realistic then Jelinski-Moranda model and provides the better reliability estimation of the software system.
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Conference papers on the topic "JELINSKI-MORANDA MODEL"

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Luo, Ziqiang, Peng Cao, Guochun Tang, and Lihua Wu. "A Modification to the Jelinski-Moranda Software Reliability Growth Model Based on Cloud Model Theory." In 2011 Seventh International Conference on Computational Intelligence and Security (CIS). IEEE, 2011. http://dx.doi.org/10.1109/cis.2011.51.

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