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.