DocumentCode :
2677456
Title :
Automated Test Oracle Based on Neural Networks
Author :
Ye, Mao ; Feng, BoQin ; Zhu, Li ; Lin, Yao
Author_Institution :
Sch. of Electron. & Inf. Eng., Xi´´an Jiaotong Univ.
Volume :
1
fYear :
2006
fDate :
17-19 July 2006
Firstpage :
517
Lastpage :
522
Abstract :
In this paper an attempt has been made to explore the possibility of the usage of artificial neural networks as automated test oracle. Automated test oracle includes capabilities to generate expected output and compare it with actual output automatically. It is important for automated software testing. But there are very few techniques to implement it. In this paper, an insensitive oracle is proposed. It generates approximate output that is close to expected output. The actual output is then compared with the approximate output in an interval. The relation between inputs and outputs of an application under testing is described as a function. When it is a continue function, neural networks are used to estimate the output after training. By the method, automated oracle can be implemented and precision be adjusted by parameters. It can save a lot of time and labor in software testing
Keywords :
neural nets; program testing; artificial neural networks; automated software testing; automated test oracle; Application software; Artificial neural networks; Automatic testing; Electronic equipment testing; Graphical user interfaces; Logic testing; Neural networks; Performance evaluation; Software testing; Table lookup; Test oracle; neural networks; software testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cognitive Informatics, 2006. ICCI 2006. 5th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
1-4244-0475-4
Type :
conf
DOI :
10.1109/COGINF.2006.365539
Filename :
4216456
Link To Document :
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