Predicting the Size of Test Suites from Use Cases: An Empirical Exploration

Software testing plays a crucial role in software quality assurance. Software testing is, however, a time and resource consuming process. It is, therefore, important to estimate as soon as possible the effort required to test software. Unfortunately, little is known about the prediction of the testing effort. The study presented in this paper aims at exploring empirically the prediction of the testing effort from use cases. We address the testing effort from the perspective of test suites size. We used four metrics to characterize the size and complexity of use cases, and three metrics to quantify different perspectives of the size of corresponding test suites. We used the univariate logistic regression analysis to evaluate the individual effect of each use case metric on the size of test suites. The multivariate logistic regression analysis was used to explore the combined effect of the use case metrics. The performance of the prediction models was evaluated using receiver operating characteristic analysis. An experimental study, using data collected from five Java case studies, is reported providing evidence that some of the use case metrics are significant predictors of the size of test suites.