Classification model for test case prioritization techniques

Regression Testing is mainly done in software maintenance aiming to assure that the changes made in the software have correctly been implemented and also to achieve the confidence that the modifications have not affected the other parts of the software. It is very costly and expensive technique. There are number of techniques present in literature that focus on achieving various testing objectives early in the process and hence reduces its cost. Despite of that, testers usually prefer only few already known techniques for test case prioritization. The main reason behind is the absence of guidelines for the selection of TCP techniques. Hence, this piece of research introduces a novel approach for classification of TCP techniques using fuzzy logic to support the efficient selection of test case prioritization techniques. This work is an extension of already proposed selection schema for test case prioritization techniques. To perform the validation of proposed approach results are compared with other classification techniques using Weka tool. The analysis clearly shows the effectiveness of proposed approach as compared to others in terms of its accuracy.