Unraveling the Impact of Code Smell Agglomerations on Code Stability
Amanda Santana, Eduardo Figueiredo, Juliana Alves Pereira · 2024
Code smells are symptoms in the source code that indicate code quality degradation and, consequently, may affect code comprehension and maintenance. Moreover, when two or more code smells occur on the same piece of code, forming an agglomeration, they may be more harmful to the code quality. Although the impact of smells in isolation is well known, the impact of their agglomeration is still underexplored. Our goal with this study is to provide evidence of how agglomerations impact code stability, i.e. we investigate if agglomeration suffers more modifications along the system evolution, and in which intensity. For this purpose, we mined two years of commit history from 30 open-source Java systems from GitHub. To analyze code stability, we considered four measurements: the number of commits, lines of modified code, rate of modified classes, and the proportion of changes. We examined these measurements from two perspectives: by system and by aggregating all system data. Additionally, we further considered how a class created/deleted in this time span impacts our results. Our main findings are: (i) classes with two or more code smells of different types change more frequently and in more intensity than classes with a single smell or no smell; (ii) the stability of the class varies greatly with the system under analysis; (iii) when a smelly class was deleted in our time range, they usually had several lines of code added until it became unsustainable. We can conclude that agglomerations change with more frequency and intensity, raising maintenance and evolution costs. Consequently, this information can be used to prioritize code refactoring.