Towards a Severity and Activity based Assessment of Code Smells

Code smells are the structural weaknesses which reside in a software system. They evolve negatively over time reducing the system quality i.e., maintainability, understandability etc. Therefore, they should be detected and prioritized based on criticality in order to be refactored. Most of the existing approaches are based on severity score, but little works have been done to include the information from changes history. Thus, we introduce a Harmfulness Model that integrates both information: severity and changes history (i.e., code smells activity). This study characterizes a god class activity based on its severity and change frequency of the JHotDraw open source system. The result indicates that there are two main activities of god class that can be assessed as active and passive smells. In fact, an active god class can be differentiated as strong, stable, and ameliorate smells while a passive god class has one type called dormant. Besides that, from severity and activity information, the model can compute the harmfulness score and also indicate the degree of harmfulness level. The harmfulness level may be useful to improve change likelihood estimation and refactoring candidates prioritization.