DocumentCode
2087573
Title
Random Testing: Evaluation of a Law Describing the Number of Faults Found
Author
Oriol, Manuel
Author_Institution
Dept. of Comput. Sci., Univ. of York, York, UK
fYear
2012
fDate
17-21 April 2012
Firstpage
201
Lastpage
210
Abstract
Automated random testing is an effective and predictable method for finding faults. While it was recently studied both in practice and in theory, no general laws were found that express the number of faults in function of the time or the number of tests performed. This article evaluates the Michaelis-Menten equation (Max * t)/(K + t) as a law for representing the number of faults found by automated random testing. Max is the number of faults it can uncover in the code, K is a constant dependent on the tested code and the strategy used and t is the number of tests. The evaluation relies on the testing of more than 6000 Java classes from the Qualitas Corpus.
Keywords
Java; fault tolerant computing; program testing; Java class; Michaelis-Menten equation; Qualitas corpus; automated random testing; faults; law evaluation; Approximation methods; Equations; Histograms; Java; Mathematical model; Runtime; Testing; automated; random; testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Testing, Verification and Validation (ICST), 2012 IEEE Fifth International Conference on
Conference_Location
Montreal, QC
Print_ISBN
978-1-4577-1906-6
Type
conf
DOI
10.1109/ICST.2012.100
Filename
6200118
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