Analysis of incorporating logistic testing-effort function into software reliability modeling

2002 ◽  
Vol 51 (3) ◽  
pp. 261-270 ◽  
Author(s):  
Chin-Yu Huang ◽  
Sy-Yen Kuo
2012 ◽  
Vol 241-244 ◽  
pp. 356-359
Author(s):  
Qian Zhao ◽  
Xian Feng Yu ◽  
Cheng Wei Zhang

Considering testing effort and imperfect debugging in reliability modeling process may further improve the fitting and prediction results of software reliability growth models (SRGMs). For describing the S-shaped varying trend of the testing-effort increasing rate more accurately, this paper first proposes a inflected S-shaped testing effort function (IS-TEF). Then this new TEF is incorporated into the inflected S-shaped NHPP SRGMs for obtaining a new NHPP SRGMs which consider S-shaped TEF (IS-TEFM-IS). Finally the IS-TEFM-IS and several comparison NHPP SRGMs are applied into two real failure data-sets respectively for investigating the fitting power of the IS-TEFM-IS. The experimental results show that the inflected S-shaped NHPP SRGM considering IS-TEF yields the best accurate estimation results than the other comparison SRGMs.


2010 ◽  
Author(s):  
N. Ahmad ◽  
M. G. M. Khan ◽  
L. S. Rafi ◽  
Swapan Paruya ◽  
Samarjit Kar ◽  
...  

2021 ◽  
Vol 9 (3) ◽  
pp. 23-41
Author(s):  
Nesar Ahmad ◽  
Aijaz Ahmad ◽  
Sheikh Umar Farooq

Software reliability growth models (SRGM) are employed to aid us in predicting and estimating reliability in the software development process. Many SRGM proposed in the past claim to be effective over previous models. While some earlier research had raised concern regarding use of delayed S-shaped SRGM, researchers later indicated that the model performs well when appropriate testing-effort function (TEF) is used. This paper proposes and evaluates an approach to incorporate the log-logistic (LL) testing-effort function into delayed S-shaped SRGMs with imperfect debugging based on non-homogeneous Poisson process (NHPP). The model parameters are estimated by weighted least square estimation (WLSE) and maximum likelihood estimation (MLE) methods. The experimental results obtained after applying the model on real data sets and statistical methods for analysis are presented. The results obtained suggest that performance of the proposed model is better than the other existing models. The authors can conclude that the log-logistic TEF is appropriate for incorporating into delayed S-shaped software reliability growth models.


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