The Analysis of Faults Detection Software Based on Improved Neural Network Algorithm
2014 ◽
Vol 602-605
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pp. 2044-2047
Keyword(s):
The large-scale software is consisted of the components which are quite different. The detection accuracy of the traditional faults detection methods for the large-scale component software is not satisfactory. This paper proposes a large-scale software faults detection methods based on improved neural network combining the features of the large-scale software by computing the stable probability and building the neural network faults detection models. The proposed method can analyze the serial faults of the large-scale software to determine the positions of the faults. The experiment and simulation results show that the improved method for large-scale software fault detection can greatly improve the accuracy.
2012 ◽
Vol 542-543
◽
pp. 1398-1402
2014 ◽
Vol 687-691
◽
pp. 1034-1037
Keyword(s):
2014 ◽
Vol 490-491
◽
pp. 1588-1591
Keyword(s):
Keyword(s):