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A logistic fault-detection software reliability model is derived.
The explicit mean value function solution of the proposed model for a logistic fault-detection rate is presented.
The explicit solution of the generalized model and a specific model with a logistic fault-detection rate function IS derived in Sect. 2.
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The results show that the proposed logistic fault-detection model fit significantly better than other existing NHPP models based on all three goodness-of-fit criteria.
The results show that the proposed logistic fault-detection model fits significantly better than all the existing NHPP models studied in this paper based on all MSE, PRR and PP criteria.
Pham et al. [26] recently discussed a new logistic software reliability model where the fault-detection rate per unit time follows a three-parameter logistic function.
In particular this paper adresses a fault taxonomy to analyze the fault-detection problem and presents a possible solution.
The first model is, called Loglog fault-detection rate, an NHPP model where the fault-detection rate is based on a loglog distribution function.
Ma et al. [87] proposed a combined approach for detection re-scoring from linear interpolation of a rule-based detection re-scoring system, a logistic regression-based detection re-scoring system, and a rank learning-based detection re-scoring system.
A fault diagnosis scheme which contains the strategies of both fault-detection and fault-evaluation is proposed in this paper.
Figure 1 Fault-detection system.
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