Random Cluster Sampling on X-Machines Test Cases

Software testing is considered one of the most expensive and critical phases of the software development. Formal testing approaches are extensively used for verifying the conformance of implementations to a given specification. These formal approaches usually generate a large amount of input test data which is costly in terms of time and effort. Techniques for reducing test input data are thus of the utmost importance. The contribution of this paper is to propose a framework for the reduction of test input data generated by a formal testing approach based on X-Machines. To achieve these objectives we have applied a well known statistical approach called Random Cluster Sampling on the test case set generated by a formal approach X-Machines. To exemplify our technique we have generated a test set for an X-Machine Microwave oven specification and then drew a sample from the test set by using the Random Cluster sampling technique. Based on the tolerated fault rate we have extracted conclusion about the accuracy of implementation.