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 :
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