DocumentCode
1566937
Title
Using back-propagation neural networks for functional software testing
Author
Wu, Lilan ; Liu, Bo ; Jin, Yi ; Xie, Xiaoyao
Author_Institution
Sch. of Math. & Comput. Sci., Guizhou Normal Univ., Guiyang
fYear
2008
Firstpage
272
Lastpage
275
Abstract
To create reliable, safe, and high quality software is the primary purpose of software testing. With the development of software engineering, functional software testing is one essential part of software testing. This paper explains that back-propagation neural networks can be used for functional software testing efficiently and significantly. In here we established a method which is sufficient to reveal the majority of software faults in functional testing. We explained how the method can be used to produce a set of test cases covering the most common functional existing in software automatically. Then we used the proposed methodology to test large-scale software systems. Based on the results, in the paper we paid more attention to more arithmetic and date mining methods for function software testing development.
Keywords
backpropagation; neural nets; program testing; software engineering; arithmetic methods; backpropagation neural networks; date mining methods; functional software testing; software engineering; software faults; Arithmetic; Automatic testing; Large-scale systems; Neural networks; Software engineering; Software quality; Software safety; Software systems; Software testing; System testing; back-propagation; neural networks; software testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Anti-counterfeiting, Security and Identification, 2008. ASID 2008. 2nd International Conference on
Conference_Location
Guiyang
Print_ISBN
978-1-4244-2584-6
Electronic_ISBN
978-1-4244-2585-3
Type
conf
DOI
10.1109/IWASID.2008.4688385
Filename
4688385
Link To Document