Cluster-based test cases prioritization and selection technique for agile regression testing

Abstract

Regression testing repeatedly executes test cases of previous builds to validate that the original features are not affected with any new changes. In recent years, regression testing has seen a remarkable progress with the increasing popularity of agile methods, which stress the central role of regression testing in maintaining software quality. The optimum case for regression testing in agile context is to run regression set at the end of each sprint and release, which requires a lot of cost and time. In this paper, we present an automated agile regression testing approach on both the sprints and release levels. The proposed approach addresses both weighted sprint test cases prioritization technique, which prioritizes test cases based on several parameters having real practical weight for testers, and Cluster-based Release Test cases Selection technique that clusters user stories based on the similarity of covered modules to solve the scalability issue. Test cases are then selected based on issues logged for failed test cases using text mining techniques. The proposed approach achieves enhancement for both the prioritization and selection of test cases for agile regression testing. Copyright © 2016 John Wiley & Sons, Ltd.