DocumentCode :
3385618
Title :
An Artificial Neural-Network-Based Approach to Software Reliability Assessment
Author :
Su, Yu-Shen ; Huang, Chin-Yu ; Chen, Yi-Shin ; Chen, Jing-Xun
Author_Institution :
Dept. of Comput. Sci., Nat. Tsing Hua Univ., Hsinchu
fYear :
2005
fDate :
21-24 Nov. 2005
Firstpage :
1
Lastpage :
6
Abstract :
In this paper, we propose an artificial neural- network-based approach for software reliability estimation and modeling. We first explain the network networks from the mathematical viewpoints of software reliability modeling. That is, we will show how to apply neural network to predict software reliability by designing different elements of neural networks. Furthermore, we will use the neural network approach to build a dynamic weighted combinational model. The applicability of proposed model is demonstrated through four real software failure data sets. From experimental results, we can see that the proposed model significantly outperforms the traditional software reliability models.
Keywords :
artificial intelligence; combinatorial mathematics; estimation theory; neural nets; software reliability; artificial neural network; dynamic weighted combinational model; software failure data sets; software reliability assessment; software reliability estimation; software reliability modeling; Aircraft; Application software; Artificial neural networks; Computer science; Mathematical model; Neural networks; Predictive models; Software design; Software reliability; Software testing; Combinational Model; Neural Network; Software Reliability; Software Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON 2005 2005 IEEE Region 10
Conference_Location :
Melbourne, Qld.
Print_ISBN :
0-7803-9311-2
Electronic_ISBN :
0-7803-9312-0
Type :
conf
DOI :
10.1109/TENCON.2005.301242
Filename :
4085352
Link To Document :
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