Enhanced regression testing technique for agile software development and continuous integration strategies

Abstract

To survive in competitive marketplaces, most organizations have adopted agile methodologies to facilitate continuous integration and faster application delivery and rely on regression testing during application development to validate the quality and reliability of the software after changes have been made. Consequently, for large projects with cost and time constraints, it is extremely difficult to determine which test cases to run at the end of each release. In this paper, a test case prioritization and selection approach is proposed to improve the quality of releases. From existing literature, we analyzed prevailing problems and proposed solution relevant to regression testing in agile practices. The proposed approach is based on two phases. First, test cases are prioritized by clustering those test cases that frequently change. In case of a tie, test cases are prioritized based on their respective failure frequencies and coverage criteria. Second, test cases with a higher frequency of failure or coverage criteria are selected. The proposed technique was validated by an empirical study on three industrial subjects. The results show that the method successfully selects an optimal test suite and increases the fault detection rate (i.e., more than 90% in the case of proposed technique and less than 50% in other techniques), which reduces the number of irrelevant test cases and avoids detecting duplicate faults. The results of evaluation metrics illustrate that the proposed technique significantly outperform (i.e., between 91 and 97%) as compared to other existing regression testing techniques (i.e., between 52 and 68%). Therefore, our model enhances the test case prioritization and selection with the ability for earlier and high fault detection. Thus, pruning out irrelevant test cases and redundant faults and enhancing the regression testing process for agile applications.