A Path-Oriented Test Data Generation Approach for Automatic Software Testing

The Clonal Selection (CS) Algorithm is an optimization algorithm based upon the clonal selection principle in the biological immune system. This paper presents a novel approach that uses CS algorithm for path-oriented test data generation. The approach takes a selected path as a target and executes sequences of operators iteratively for test case to generate. An affinity function which is made up of a similarity and penalty value is developed to guide the test generator to make successive modifications of the test data, so that test data can ever closer to satisfy the requirement. The comparison results show that this approach is more efficient than those based on other heuristic algorithms in finding solutions.