Multi-Objective based test case selection and prioritization for distributed cloud environment

Software testing is highly significant during the software development lifecycle for the earlier detection of errors and bugs. Test suite optimization is a selection of the smallest subset of the test cases. This enables quick recovery of the faults in the software product within a minimum time. Selection and prioritization of the test cases are the main approaches to solve the issues in the test case optimization. Various selection and prioritization techniques are developed in the recent days. However, the existing techniques require more cost and time consumption. Also, the increase in the number of objectives reduces the performance of the existing techniques. This paper proposes a multi-objective based test case selection and prioritization for distributed cloud environment. The Resemblance-Based Cluster Head (RBCH) algorithm is proposed to select the Cluster Head (CH) based on the overall similarity between the test cases. The Distance-Based Transposition (DBT) is proposed to prioritize the optimal test case clusters in the distributed environment. This proposed approach efficiently minimizes the time consumption for the testing process by reducing the number of iterations in the test case searching process. From the experimental result, it is observed that the proposed approach achieves higher fault detection rate, prioritization accuracy and lower execution time than the existing prioritization techniques.