Assessment of Code Smells for Predicting Class Change Proneness

摘要

Poor design choices called anti-patterns manifest themselves in the source code as code smells. Code smell is a synonym for bad implementation and is assumed to make maintenance tasks difficult to perform. In this study, the authors attempt to empirically validate whether it is possible to determine the degree of change proneness for a class on the basis of certain code smells in an object-oriented system. In this study, they develop a tool to detect the presence of 13 different code smells in a Java class using thresholds. The data used for assessment are the source code of Quartz, an open source job scheduler, from versions 1.5.2 and 1.6.6. A total of 79 classes are examined in this study. The results suggest a clear relationship between code smells and change proneness of a class.