Effect of Coupling on Software Faults: An Empirical Study

Abstract

Software product's quality is one of the important aspects that affect the user, the developer, and the product. Measuring quality in the early phases of the project life cycle is a major goal of project planning. Accordingly, several research studies have been proposed to measure the software product quality attributes. In this paper, we empirically study the impact of afferent coupling (Ca), efferent coupling (Ce) and coupling between object (CBO) metrics on fault prediction using bivariate correlation. We built a prediction model using these metrics to predict faults by using multivariate logistic linear regression. A case study of an open source object oriented systems is used to evaluate the correlation between coupling metrics and faults. The results indicate that the efferent coupling (Ce) is a better indicator for fault prediction than afferent coupling (Ca) and CBO (coupling between object).