Many tools for code smell detection have been devel- oped, 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.
ARCELLI FONTANA, F., Ferme, V., Zanoni, M. (2015). Poster: Filtering Code Smells Detection Results. In 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering (ICSE). Proceedings (pp.803-804). IEEE Computer Society [10.1109/ICSE.2015.256].
Poster: Filtering Code Smells Detection Results
ARCELLI FONTANA, FRANCESCAPrimo
;ZANONI, MARCOUltimo
2015
Abstract
Many tools for code smell detection have been devel- oped, 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.
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