Developers constantly perform code changes throughout the lifetime of a project. These changes may induce the introduction of design decay over time. Design decay may be reduced or accelerated by interacting factors that underlie each change. These factors may come from specific actions of change or repair – e.g., refactorings – to how developers contribute and discuss the changes. However, existing studies do not explain how these factors interact and influence design decay. They solely tend to focus on a few types of factors, and often consider them in isolation. Interactions between factors may cause different outcomes than those previously studied. Studying factors in isolation may not properly explain what are the most relevant set of interacting factors that influence design decay. This may indicate that existing approaches to avoid or mitigate design decay are misleading since they do not consider potentially relevant interactions between various factors. Thus, this dissertation reports an investigation that aims to increase the understanding of how a wide range of interacting factors can influence design decay in order to facilitate the investigation of which practices can be used to avoid or mitigate design decay. To this end, we performed an in-depth analysis to fill knowledge gaps on two types of factors: process-related (i.e., related to changes and their produced outcomes) and developer-related (i.e., related to the developer working on the changes) factors. We focused on analyzing the effects of potential interactions between the aforementioned factors and 12 sub-factors with regards to how they affected modules with different levels of decay. We observed diverging decay patterns in these modules. Our results indicate that both types of factors can be used to distinguish between different decay levels in classes. We have also observed that: (1) individually, the developer-related subfactor that represented first-time contributors, as well as the process-related one that represented size of the changes, did not exert negative effects on the changed classes. However, when analyzing specific factor interactions, we saw that changes where both of these factors interacted tended to have a negative effect and led to decay. Interestingly, this behaviour did not alter even when the change was introduced via pull request (which usually triggers a code review process); (2) surprisingly, extraction-type refactorings often do not have a positive effect on code quality, while, by contrast, move refactorings were mostly positive. We also discuss how these findings in this dissertation can aid developers and researchers in improving their guidelines for the avoidance and monitoring of design decay.