On allocation of resources during testing phase incorporating flexible Software Reliability Growth Model with testing effort under Dynamic Environment

2018 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
P.K. Kapur ◽  
Naman Taneja ◽  
Ramita Sahni ◽  
Vijay Kumar
Keyword(s):  
Growth Model ◽  
Software Reliability ◽  
Dynamic Environment ◽  
Reliability Growth ◽  
Allocation Of Resources ◽  
Software Reliability Growth Model ◽  
Testing Phase ◽  
Testing Effort ◽  
Software Reliability Growth

scholarly journals Stochastic Differential Equation-Based Flexible Software Reliability Growth Model

2009 ◽  
Vol 2009 ◽  
pp. 1-15 ◽  
Author(s):  
P. K. Kapur ◽  
Sameer Anand ◽  
Shigeru Yamada ◽  
Venkata S. S. Yadavalli
Keyword(s):  
Differential Equation ◽  
Stochastic Differential Equation ◽  
Growth Model ◽  
Software Reliability ◽  
Error Detection ◽  
Reliability Growth ◽  
Software Reliability Growth Model ◽  
Testing Phase ◽  
Continuous State ◽  
Software Reliability Growth

Several software reliability growth models (SRGMs) have been developed by software developers in tracking and measuring the growth of reliability. As the size of software system is large and the number of faults detected during the testing phase becomes large, so the change of the number of faults that are detected and removed through each debugging becomes sufficiently small compared with the initial fault content at the beginning of the testing phase. In such a situation, we can model the software fault detection process as a stochastic process with continuous state space. In this paper, we propose a new software reliability growth model based on Itô type of stochastic differential equation. We consider an SDE-based generalized Erlang model with logistic error detection function. The model is estimated and validated on real-life data sets cited in literature to show its flexibility. The proposed model integrated with the concept of stochastic differential equation performs comparatively better than the existing NHPP-based models.

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