Test Predictive Model: Under/Over Prediction Of Test Case Size Estimation

Abstract

The process of developing an estimation of adequate test set size utilising the test predictive model is presented and evaluated in this paper. The strategy to develop the model was previously presented in our different paper, whereas the details, design, and implementation idea for the model are described in this paper. The aims of the prediction model is to solve the problems related with the size of the test cases. For better fault detection in the retesting process, a good prediction of the size of test cases is required. Too few or too large a consumption of test cases may increase the budget and time in the tesing process. This model could potentially test the set constuction as an important factor that can provide an accuracy estimation of potential faults that will occur in the system based on a reliable guess (of a number) of the (good) adequacy of the test case in relation to the detected error. The essential elements for developing the model are explained in detail in the subsequent section. The evaluation conducted in this chapter includes a few steps, which are then applied in one real case study to reveal the effectiveness of the proposed prediction design model. The test predictive model is then evaluated for over-prediction or under-prediction compared to manual estimation by experts and then further evaluated using a seed fault analysis.