DocumentCode :
2929629
Title :
Probabilistic Adaptive Random Testing
Author :
Chan, Kwok Ping ; Chen, T.Y. ; Towey, Dave
Author_Institution :
Dept. of Comput. Sci., Hong Kong Univ.
fYear :
2006
fDate :
27-28 Oct. 2006
Firstpage :
274
Lastpage :
280
Abstract :
Adaptive random testing (ART) methods are software testing methods which are based on random testing, but which use additional mechanisms to ensure more even and widespread distributions of test cases over an input domain. Restricted random testing (RRT) is a version of ART which uses exclusion regions and restricts test case generation to outside of these regions. RRT has been found to perform very well, but its use of strict exclusion regions (from within which test cases cannot be generated) has prompted an investigation into the possibility of modifying the RRT method such that all portions of the input domain remain available for test case generation throughout the duration of the algorithm. In this paper, we present a probabilistic approach, probabilistic ART (PART), and explain two different implementations. Preliminary empirical data supporting the methods is also examined
Keywords :
probability; program testing; exclusion regions; probabilistic adaptive random testing; restricted random testing; software testing; test case generation; Application software; Australia; Communications technology; Computer science; Performance evaluation; Software testing; Statistical analysis; Subspace constraints;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Quality Software, 2006. QSIC 2006. Sixth International Conference on
Conference_Location :
Beijing
ISSN :
1550-6002
Print_ISBN :
0-7695-2718-3
Type :
conf
DOI :
10.1109/QSIC.2006.48
Filename :
4032295
Link To Document :
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