A Bootstrapping Approach for Software Reliability Measurement Based on a Discretized NHPP Model

Inoue, Shinji; Yamada, Shigeru

doi:10.4236/jsea.2013.64a001

Cited by 2 publications

(1 citation statement)

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“…An improved additive model to reliability estimation of modular structure-based software is there to study [23]. Inoue and Yamada discussed discrete software reliability measurement based on a discredited (NHPP) model [24]. Kiyoshi Honda prosposed a stochastic process based software reliability model [25], and Kim HeeCheul proposed a comparative problem of a reliability model for Lomax and Gompertz distribution property [26].…”

Section: Related Workmentioning

confidence: 99%

A New Variant of JM Software Reliability Model

Kaswan

Choudhary

Singh

et al. 2022

Scientific Programming

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Software reliability is the probability of failure-free operations of software in a specific environment in a given time period. Various software reliability models have been designed by the researchers, but the JM model is the first influential model. The JM model was developed with the basic assumption that the faults are independent in this model and the debugging process is perfect. But practically, all debugging processes may not be perfect, especially when the faults are dependent; in this case, the fault that is actually to have been removed may also remove more than one fault and cause it to add some new faults. To handle this behavior of faults mutual dependency, we need a new model which may be less reliable or the result accuracy of the model may be lower than that of the existing ones, but it can handle more practical situations in the fault removal process. In this paper, we proposed a new software reliability model with the same assumption that at whatever time a failure is detected, it is not completely eradicated and there is a possibility of raising some new faults because of wrong analysis or inaccurate modifications in the software or the removal of the existing fault may also remove some other faults. The proposed model is more practical than the existing ones.

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Section: Related Workmentioning

confidence: 99%