Adaptive random testing through iterative partitioning revisited
Johannes Mayer, Tsong Yueh Chen, De Huang · 2006
Recently, Adaptive Random Testing through Iterative Partitioning (IP-ART) has been proposed as a random testing method that is more effective than pure Random Testing. Besides this, it is supposed to be equally effective as very good random testing techniques, namely Distance-Based Adaptive Random Testing and Restricted Random Testing, while only having between linear and quadratic runtime. In the present paper, it is investigated what influence the ratio of width and height of a rectangular input domain has on the effectiveness of various Adaptive Random Testing methods. Based on our findings, an improved version of IP-ART is proposed. The effectiveness of the new method is also analyzed for various ratios of width and height of the input domain.