An Application of Association Rule Mining to Unit Test Selection

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dc.contributor.authorGunderson, Karl Nils
dc.date.accessioned2013-07-16T19:03:57Z
dc.date.available2013-07-16T19:03:57Z
dc.date.issued2013
dc.description.abstractAppropriate selection of unit tests during the software development process is vital when many unit tests exist. The developer may be unfamiliar with some tests and non-obvious relationships between application code and test code may exist. Poor test selection may lead to defects. This is especially true when the application is large and many developers are involved. By the application of association rule mining to the unit test selection process and by comparison with extant selection techniques, we will provide a quantitative analysis of the benefits of heuristic and its limit to development where process patterns are stable.en_US
dc.identifier.urihttp://hdl.handle.net/10365/23042
dc.publisherNorth Dakota State Universityen_US
dc.rightsNDSU Policy 190.6.2
dc.rights.urihttps://www.ndsu.edu/fileadmin/policy/190.pdf
dc.subject.lcshComputer software -- Testing.en_US
dc.subject.lcshComputer software -- Validation.en_US
dc.subject.lcshComputer software -- Verification.en_US
dc.subject.lcshAssociation rule mining.en_US
dc.titleAn Application of Association Rule Mining to Unit Test Selectionen_US
dc.typeMaster's paperen_US
ndsu.advisorDo, Hyunsook
ndsu.collegeEngineeringen_US
ndsu.degreeMaster of Science (MS)en_US
ndsu.departmentComputer Scienceen_US
ndsu.programComputer Scienceen_US

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