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GECCO
2006
Springer

Towards effective adaptive random testing for higher-dimensional input domains

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Towards effective adaptive random testing for higher-dimensional input domains
Adaptive Random Testing subsumes a class of algorithms that detect the first failure with less test cases than Random Testing. The present paper shows that a "reference method" in the field of Adaptive Random Testing is not effective for higher dimensional input domains and clustered failure-causing inputs. The reason for this behavior is explained, and a modified method is proposed and analyzed. Categories and Subject Descriptors D.2.5 [Software Engineering]: Testing and Debugging-Testing tools; G.3 [Probability and Statistics]: Reliability and life testing General Terms Algorithms, Reliability, Verification Keywords Adaptive Random Testing, Random Testing, Test case selection
Johannes Mayer
Added 23 Aug 2010
Updated 23 Aug 2010
Type Conference
Year 2006
Where GECCO
Authors Johannes Mayer
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