DocumentCode
147935
Title
Techniques for Automatic Detection of Metamorphic Relations
Author
Kanewala, Upulee
Author_Institution
Comput. Sci. Dept., Colorado State Univ., Fort Collins, CO, USA
fYear
2014
fDate
March 31 2014-April 4 2014
Firstpage
237
Lastpage
238
Abstract
Much software lacks test oracles, which limits automated testing. Metamorphic testing is one proposed method for automating the testing process for programs without test oracles. Unfortunately, finding appropriate metamorphic relations for use in metamorphic testing remains a labor intensive task, which is generally performed by a domain expert or a programmer. We are investigating novel approaches for automatically predicting metamorphic relations using machine learning techniques. Preliminary results show that the proposed techniques are highly effective in predicting metamorphic relations.
Keywords
automatic testing; learning (artificial intelligence); program testing; automated software testing; automatic metamorphic relation detection techniques; machine learning techniques; metamorphic testing; Accuracy; Feature extraction; Kernel; Predictive models; Support vector machines; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Testing, Verification and Validation Workshops (ICSTW), 2014 IEEE Seventh International Conference on
Conference_Location
Cleveland, OH
Type
conf
DOI
10.1109/ICSTW.2014.62
Filename
6825666
Link To Document