DocumentCode :
1785802
Title :
Software test case generation & test oracle design using neural network
Author :
Majma, Negar ; Babamir, Seyed Morteza
Author_Institution :
Dept. of Comput., Univ. of Kashan, Kashan, Iran
fYear :
2014
fDate :
20-22 May 2014
Firstpage :
1168
Lastpage :
1173
Abstract :
White Box and Black Box testing are two major approaches to software testing where the former uses software source code and the latter uses software specification and focuses on testing functional requirements. In this paper, we aim to present an automated method in which a combination of White and Black Box testing is presented using Neural Networks. In order to testify the effectiveness of our proposed approach, experimental results obtained from applying our method to 6 benchmark case studies and as well as one real application from NIST SAMATE dataset are presented.
Keywords :
neural nets; program testing; NIST SAMATE dataset; automated method; black box testing; functional requirements testing; neural network; software source code; software specification; software test case generation; software testing; test oracle design; white box testing; Biological neural networks; Software; Software testing; Training; Vectors; Oracle of software; Software testing; neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Engineering (ICEE), 2014 22nd Iranian Conference on
Conference_Location :
Tehran
Type :
conf
DOI :
10.1109/IranianCEE.2014.6999712
Filename :
6999712
Link To Document :
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