On the relationships between the distribution of failure-causing inputs and effectiveness of adaptive random testing

Recently, adaptive random testing (ART) has been developed to enhance the fault-detection effectiveness of random testing (RT). It has been known in generalities that the fault-detection effectiveness of ART depends on the distribution of failure-causing inputs, yet this understanding is in coarse terms without precise details. In this paper, we conduct an in-depth investigation into the factors that have an impact on the fault-detection effectiveness of ART. This paper gives a comprehensive analysis of the favourable conditions for ART and, hence, provides a guideline for testers to decide when to use ART instead of RT.