Title :
Software fault prediction based on grey neural network
Author :
Zhang, Peng ; Chang, Yu-tong
Author_Institution :
Eng. Inst., Air Force Eng. Univ., Xi´´an, China
Abstract :
Considering determining the number of software fault is an uncertain non-linear problem with only small sample, a novel software fault prediction method based on grey neural network is put forward. Firstly, constructing the grey neural network topological structure according the small sample sequence is necessary, and then the network learning algorithm is discussed. Finally, the grey neural network prediction model based on the grey theory and artificial neural network is proposed. The sample fault sequences of some software project are used to verify the precision of this method. Comparison with GM(1,1), the proposed model can reduce the prediction relative error effectively.
Keywords :
grey systems; neural nets; software fault tolerance; artificial neural network; grey neural network topological structure; network learning algorithm; small sample sequence; software fault number; software fault prediction; uncertain nonlinear problem; Neural networks; Prediction algorithms; Predictive models; Software; Software algorithms; Training; Fault Prediction; Grey Neural Network; Software;
Conference_Titel :
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4577-2130-4
DOI :
10.1109/ICNC.2012.6234505