  Bad smells have been defined to describe potential problems in code, possibly
pointing out refactoring opportunities. Several empirical studies have
highlighted that smells have a negative impact on comprehension and
maintainability. Consequently, several approaches have been proposed to detect
and restructure them. However, studies on the inter-relationship of occurrence
of different types of smells in source code are still lacking, especially those
focused on the quantification of this inter-relationship. In this work, we aim
at understand and quantify the possible the inter-relation of smells Large
Class - LC, Complex Class - CC and Duplicate Code - DC. In particular, we
investigate patterns of LC and CC regarding the presence or absence of
duplicate code. We conduct a quantitative study on five open source projects,
and also a qualitative analysis to measure and understand the association of
specific smells. As one of the main results, we highlight that there are
"occurrence patterns" among these smells, for example: either in Complex Class
or in the co-occurrence of Large Class and Complex Class, clones tend to be
more prevalent in highly complex classes than less complex classes. The found
patterns could be used to improve the performance of detection tools or even
help in refactoring tasks.
