ABSTRACT

Automated test case generation is an efficient approach for software testing. Slicing of program provides ease to testability and enhances debugging capacity. To generate the dynamic slice, slicing criterion is required in which the input data parameter is the essential component. Most of the research work focuses on deriving the input by random consideration but it simply takes a longest period of time to generate slices that provides the path coverage of Unit Under Test (UUT). This paper generates the optimal test cases by using Genetic Algorithm (GA) and Control Flow Graph (CFG), these test cases cover all the independent path present in the CFG. The optimal test cases are supplied as input component of the dynamic slicing criteria. So the dynamic slice criteria that use these optimal test cases as the input generates the efficient dynamic slice set that is helpful in efficient testing and efficient debugging. Here two approaches, first the dynamic slice using node marking and the second by using relevant sets are discussed according to optimal test cases as input component.