Abstract
In this paper, we investigate empirically the relationship between object-oriented design metrics and testability of classes. We address testability from the point of view of unit testing effort. We collected data from three open source Java software systems for which JUnit test cases exist. To capture the testing effort of classes, we used metrics to quantify the corresponding JUnit test cases. Classes were classified, according to the required unit testing effort, in two categories: high and low. In order to evaluate the relationship between object-oriented design metrics and unit testing effort of classes, we used logistic regression methods. We used the univariate logistic regression analysis to evaluate the individual effect of each metric on the unit testing effort of classes. The multivariate logistic regression analysis was used to explore the combined effect of the metrics. The performance of the prediction models was evaluated using Receiver Operating Characteristic analysis. The results indicate that: 1) complexity, size, cohesion and (to some extent) coupling were found significant predictors of the unit testing effort of classes and 2) multivariate regression models based on object-oriented design metrics are able to accurately predict the unit testing effort of classes.
Highlights
Software testability is an important software quality attribute
The results show that multivariate regression models based on OO metrics are able to accurately predict the unit testing effort of classes
The AUC values (WMC: 0.798, LOC: 0.793 and LCOM: 0.73) confirm that univariate Logistic Regression (LR) models based on the metrics WMC, LOC and LCOM are more predictive of testing effort than the other OO metrics
Summary
Software testability is an important software quality attribute. IEEE [1] defines testability as the degree to which a system or component facilitates the establishment of test criteria and the performance of tests to determine whether those criteria have been met. According to Baudry et al [3,4], software testability is influenced by many factors including controllability, observability and the global test cost. Yeh et al [5] argue that diverse factors such as control flow, data flow, complexity and size contribute to testability. Dealing with software testability raises several questions such as [7,8]: Why is one class easier to test than another? According to Baudry et al testability becomes crucial in the case of object-oriented (OO) software systems where control flows are generally not hierarchical, but diffuse and distributed over whole architecture [3,4] Dealing with software testability raises several questions such as [7,8]: Why is one class easier to test than another? What makes a class hard to test? What contributes to the testability of a class? How can we quantify this notion? In addition, according to Baudry et al testability becomes crucial in the case of object-oriented (OO) software systems where control flows are generally not hierarchical, but diffuse and distributed over whole architecture [3,4]
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