A Study on Association Rule Mining Based Software Design Defect Detection
نویسنده
چکیده
In this paper we are investigating the effect of parameter variations for a method we have previously introduced for detecting software design defects. This method uses software metrics and relational association rules to find badly designed classes. We perform five different studies, to see the effect of using normalized or original software metric values, the effect of mining only binary or any-length rules, the effect of mining only maximal or all rules and the effect of changing the value of the minimum support for the rules. We are also investigating the changes caused by modifying the value of the parameter that determines which classes to report as having bad design.
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