Enhancing mirror adaptive random testing through dynamic partitioning

摘要

Context: Adaptive random testing (ART), originally proposed as an enhancement of random testing, is often criticized for the high computation overhead of many ART algorithms. Mirror ART (MART) is a novel approach that can be generally applied to improve the efficiency of various ART algorithms based on the combination of "divide-and-conquer" and "heuristic" strategies.