Exploring the relationships between the understandability of components in architectural component models and component level metrics

Abstract

Architectural component models represent high level designs and are frequently used as a central view of architectural descriptions of software systems. The components in those models represent important high level organization units that group other components and classes in object-oriented design views. Hence, understandability of components and their interactions plays a key role in supporting the architectural understanding of a software system. In this paper we present a study we carried out to examine the relationships between the effort required to understand a component, measured through the time that participants spent on studying a component, and component level metrics that describe component's size, complexity and coupling in terms of the number of classes in a component and the classes' relationships. The participants were 49 master students, and they had to fully understand the components' functionalities in order to answer 4 true/false questions for each of the 7 components in the architecture of the Soomla Android store system. Correlation, collinearity and multivariate regression analysis were performed. The results of the analysis show a statistically significant correlation between three of the metrics, number of classes, number of incoming dependencies, and number of internal dependencies, on one side, and the effort required to understand a component, on the other side. In a multivariate regression analysis we obtained 3 reasonably well-fitting models that can be used to estimate the effort required to understand a component. In our future work we plan to study more components and investigate more metrics and their relationships to the understandability of components and architectural component models.