Using Wavelet Support Vector Machines to Generate Expected Outputs

Author

Ye, Mao ; Feng, BoQin ; Zhu, Li ; Lin, Yao

Author_Institution

Sch. of Electron. & Inf. Eng., Xi´´an Jiaotong Univ.

Volume

2

fYear

2006

fDate

17-19 July 2006

Firstpage

886

Lastpage

890

Abstract

A test case consists of a set of inputs and a list of expected outputs. To automatically generate the expected outputs for the test case is rather difficult. An approach based on wavelet support vector machines (WSVM) is proposed to overcome it. After training, WSVM is used to automatically generate the expected outputs, which approximate the correct outputs. Actual outputs of the application under testing (AUT) are then compared with expected outputs in an interval to determine if there is a failure. Experiment and comparison show that the method is effective and can save a lot of time and labor in software testing

Keywords

program testing; support vector machines; wavelet transforms; application under testing; software testing; wavelet support vector machines; Application software; Automatic testing; Electronic equipment testing; Graphical user interfaces; Kernel; Neural networks; Software performance; Software testing; Support vector machine classification; Support vector machines; Support vector machines; software testing; wavelet kernel function;

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.2006.365609

Filename

4216527