Abstract
Code smells are considered to be indicators of design flaws or problems in source code. Various tools and techniques have been proposed for detecting code smells. The number of code smells detected by these tools is generally large, so approaches have also been developed for prioritizing and filtering code smells. However, the lack of empirical data regarding how developers select and prioritize code smells hinders improvements to these approaches. In this study, we investigated professional developers to determine the factors they use for selecting and prioritizing code smells. We found that Task relevance and Smell severity were most commonly considered during code smell selection, while Module importance and Task relevance were employed most often for code smell prioritization. These results may facilitate further research into code smell detection, prioritization, and filtration to better focus on the actual needs of developers.
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