Random Border Mirror Transform: A Diversity Based Approach to an Effective and Efficient Mirror Adaptive Random Testing

Mirror Adaptive random testing (MART) is an overhead reduction strategy for adaptive random testing methods. Theoretically speaking, MART's advantage over ordinary ARTs is determined by the mirroring scheme selected. Incidentally, an inherent problem with MART relates to the difficulty in the choice of a scheme for any testing task. This is because a higher scheme (larger mirror domains) does not necessarily guarantee efficient utilization of testing resources due to lack of diversity of mirror generated test cases. The culprit has been identified as the mapping functions used as substitutes to complex ART methods. In this paper, we present a new method for generating diversified mirror test cases by randomly displacing the mirror partitions upon which the mapping functions of MART operates. The result of simulations and experiments conducted shows remarkable improvement over MART's effectiveness and efficiency across MART schemes, especially where program failures are unrelated to one or more input parameters.