A Sensitivity Analysis of a New NHPP Software Reliability Model with the Generalized Exponential Fault Detection Rate Function Considering the Uncertainty of Operating Environments

2020 ◽  
Vol 22 (2) ◽  
pp. 473-482
Author(s):  
Yoon Song Kwang ◽  
In Hong Chang
Keyword(s):  
Sensitivity Analysis ◽  
Fault Detection ◽  
Software Reliability ◽  
Detection Rate ◽  
Rate Function ◽  
Reliability Model ◽  
Software Reliability Model ◽  
Operating Environments

scholarly journals NHPP Software Reliability Model with Inflection Factor of the Fault Detection Rate Considering the Uncertainty of Software Operating Environments and Predictive Analysis

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 521 ◽  
Author(s):  
Song ◽  
Chang ◽  
Pham
Keyword(s):  
Fault Detection ◽  
Software Reliability ◽  
Detection Rate ◽  
The Other ◽  
Reliability Model ◽  
New Model ◽  
Software Failures ◽  
Software Failure ◽  
Software Reliability Model ◽  
Operating Environments

The non-homogeneous Poisson process (NHPP) software has a crucial role in computer systems. Furthermore, the software is used in various environments. It was developed and tested in a controlled environment, while real-world operating environments may be different. Accordingly, the uncertainty of the operating environment must be considered. Moreover, predicting software failures is commonly an important part of study, not only for software developers, but also for companies and research institutes. Software reliability model can measure and predict the number of software failures, software failure intervals, software reliability, and failure rates. In this paper, we propose a new model with an inflection factor of the fault detection rate function, considering the uncertainty of operating environments and analyzing how the predicted value of the proposed new model is different than the other models. We compare the proposed model with several existing NHPP software reliability models using real software failure datasets based on ten criteria. The results show that the proposed new model has significantly better goodness-of-fit and predictability than the other models.

scholarly journals A Software Reliability Model with a Weibull Fault Detection Rate Function Subject to Operating Environments

2017 ◽  
Author(s):  
Kwang Yoon Song ◽  
In Hong Chang ◽  
Hoang Pham
Keyword(s):  
Software Reliability ◽  
Goodness Of Fit ◽  
Rate Function ◽  
Mean Value ◽  
Software Systems ◽  
Reliability Model ◽  
Function Solution ◽  
Software Reliability Model ◽  
Operating Environments ◽  
Proposed Model

The main focus when developing software is to improve the reliability and stability of a software system. When software systems are introduced, these systems are used in field environments that are the same as or close to those used in the development-testing environment; however, they may also be used in many different locations that may differ from the environment in which they were developed and tested. In this paper, we propose a new software reliability model that takes into account the uncertainty of operating environments. The explicit mean value function solution for the proposed model is presented. Examples are presented to illustrate the goodness-of-fit of the proposed model and several existing non-homogeneous Poisson process (NHPP) models and confidence intervals of all models based on two sets of failure data collected from software applications. The results show that the proposed model fits the data more closely than other existing NHPP models to a significant extent.

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