DocumentCode :
2210281
Title :
Predication of Program Behaviours for Functionality Testing
Author :
Jin, Hu ; Wang, Yi ; Chen, Nian-Wei ; Wang, Shuo ; Zeng, Ling-Ming
Author_Institution :
Comput. Sci. Dept., Chengdu Univ. of Inf. Technol., Chengdu, China
fYear :
2009
fDate :
26-28 Dec. 2009
Firstpage :
4993
Lastpage :
4996
Abstract :
Functionality Testing is one of the most popular used technologies of black-box testing strategy. Programs to be test were taken as implicit functions mapping inputs into outs. In the view of functionality testing, if the functional behaviors of the program can be predicated correctly, it could be applied as test oracles for newer test cases generation. The main problems of this issue are discussed as: firstly, collecting test data for the software being tested on the base of covering its functionalities. Secondly, training Self-Organized-Feature-Mapping networks with the attained data set to simulate and predicate program behaviors. Thirdly, generating test oracles with the pre-described networks that is able to predicate program behaviors with unknown inputs automatically. Lastly, designing and doing experiments to validate the effectiveness of such method. This article concludes that by simulating the program behaviors with properly designed ANN can provide valuable clues for automatic functionality testing.
Keywords :
program testing; self-organising feature maps; automatic functionality testing; black-box testing strategy; program functional behaviors; self-organized feature mapping networks; software testing; test oracles; Artificial neural networks; Automatic testing; Computational modeling; Computer science; Costs; Information science; Information technology; Programming profession; Software quality; Software testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Engineering (ICISE), 2009 1st International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4909-5
Type :
conf
DOI :
10.1109/ICISE.2009.843
Filename :
5454627
Link To Document :
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