Object Distance and Its Application to Adaptive Random Testing of Object-Oriented Programs

Testing with random inputs can give surprisingly good results if the distribution of inputs is spread out evenly over the input domain; this is the intuition behind Adaptive Random Testing, which relies on a notion of "Distance" between test values. Such distances have so far been defined for integers and other elementary inputs; extending the idea to the testing of today's object-oriented programs requires a more general notion of distance, applicable to composite programmer-defined types. The authors define a notion of object distance, with associated algorithms to compute distances between arbitrary objects, and use it to generalize Adaptive Random Testing to such inputs.