Parameterized and Prioritized (P2M-TCP) Cloud Testing Approach for Optimized Fault Detection Rate (FDR)

Abstract

Cloud Testing is one of the prominent areas to estimate functionality of the Software. It is the process of evaluating the quality of resources in the cloud environment. According to the prior studies, 50% of the performance issues in Cloud Software testing are faced due to the minimum optimal utilization of time, cost and effort. Software testing required dedicated infrastructure which becomes unaffordable for Small-Medium Scale Industry (SMSI). As per the requirements of SMSI, moving testing to cloud would deduct the cost of acquiring required infrastructure. The optimized cloud testing aims to detect maximum faults which could result in evaluation of High Fault Detection Rate (FDR). The research proposed P2M-TCP (Parameterized and Prioritized: Mutation Testing-Test Case Prioritization) approach for testing a software in cloud environment. The objective of the research is to improvise testing by achieving higher fault detection rate through the amalgamation of mutation testing and test case prioritization. The proposed research performs cloud testing based on two approaches, Mutation Testing and Test Case Prioritization. In mutation, the program assertions are mutated to achieve higher code coverage for maximum fault detection and TCP is applied on test cases produced against mutated code based on Occurrence Probability, Severity, Functional Interactivity. The focus of the proposed approach is to achieve higher fault detection rate by prioritizing test cases on the basis of test case execution history and other identified parameters. The current study implements the Parameterized and Prioritization approach to enhance cloud testing performance. The uniqueness of the proposed framework is revealed by comparison of the proposed framework with existing techniques used in other studies.