Optimal test case prioritization in cloud based regression testing with aid of KFCM

Abstract

Regression testing is a kind of software testing that authenticates that software previously developed and established still accomplishes correctly after it was altered or interfaced with other software. The aim of the investigation is to progress the software competence via cloud based regression testing. The projected technique has three chief stages such as, 1) test case generation, 2) clustering and 3) test case prioritization. Primarily the input implementation is send to the cloud for test case generation. For producing the test cases the projected method utilizes coverage metrics. Following the test case generation, the existing test cases are gathered with the help of kernel fuzzy c means clustering algorithm. Subsequently each group is fed to test case prioritization; in that grey wolf optimization algorithm is utilized for test case prioritization. Thus we will get operative prioritized test cases. Our method will be implemented on JAVA with Cloud Sim platform. The presentation will be assessed using execution time and memory use. From the solution the applied method precedes minimum implementation time associated with the available technique.