Poster: Filtering Code Smells Detection Results

Many tools for code smell detection have been developed, providing often different results. This is due to the informal definition of code smells and to the subjective interpretation of them. Usually, aspects related to the domain, size, and design of the system are not taken into account when detecting and analyzing smells. These aspects can be used to filter out the noise and achieve more relevant results. In this paper, we propose different filters that we have identified for five code smells. We provide two kind of filters, Strong and Weak Filters, that can be integrated as part of a detection approach.