Increasing test coverage using human-based approach of fault injection testing

Abstract

Fault injection testing (FIT) approach validates system's fault tolerance mechanism by actively injecting software faults into the targeted areas in the system in order to accelerate its failure rate. This highly complements other testing approaches such as requirements and regression testing implemented during the same testing phase. During testing, it is impossible to run all possible test scenarios. It is especially difficult to predict how the user might use the system functionality correctly as per design. The human interaction through the system may be varies and will leads to the functionality loophole. It is therefore important to have strategic testing approach for evaluating the dependability of computer systems especially in human errors. This paper proposed on applying Knowledge-Based, Fault Prediction Model and Test Case Prioritization approaches that can be combined to increase the test coverage. The goal of this paper is to highlight the needs and advantages of the selected approaches in performing FIT as one of effective testing techniques in the ongoing quest for increased software quality.