An improved genetic approach for test path generation

Quality of a software system depends on testing approaches adopted to analyze the software product. Testing process itself depends on two main vectors called test sequence generation and test data generation. Test sequence generation is about to identify the order in which the particular test cases will be executed and the test data defines the various checks performed on each test case. In this present work, a fuzzy improved genetic approach is suggested for test case generation. The sequence on these test cases is here dependent on module interaction analysis. Based on this analysis, the test case prioritization will be defined. Once the test cases will be prioritized, the next work is to apply fuzzy improved genetic approach for test path generation. The work is analyzed under different prioritization vectors. Analysis of work is defined in terms of test cost estimation under different prioritization scenarios.