Applying software metric thresholds for detection of bad smells

Software metrics can be an effective measurement tool to assess the quality of software. In the literature, there are a lot of software metrics applicable to systems implemented in different paradigms like Objects Oriented Programming (OOP). To guide the use of these metrics in the evaluation of the quality of software systems, it is important to define their thresholds. The aim of this study is to investigate the effectiveness of the thresholds in the evaluation of the quality of object oriented software. To do that, we used a threshold catalog of 18 software metrics derived from 100 software systems to define detection strategies for five bad smells. They are: Large Class, Long Method, Data Class, Feature Envy and Refused Bequest. We investigate the effectiveness of the thresholds in detection analysis of 12 software systems using these strategies. The results obtained by the proposed strategies were compared with the results obtained by the tools JDeodorant and JSPiRIT, used to identify bad smells. This study shows that the metric thresholds were significantly effective in supporting the detection of bad smells.

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