Finding focused itemsets from software defect data

Software product measures have been widely used to predict software defects. Though these measures help develop good classification models, studies propose that relationship between software measures and defects still needs to be investigated. This paper investigates the relationship between software measures and the defect prone modules by studying associations between the two. The paper identifies the critical ranges of the software measures that are strongly associated with defects across five datasets of PROMISE repository. The paper also identifies the ranges of the measures that do not necessarily contribute towards defects. These results are supported by information gain based ranking of software measures.