MULTI-OBJECTIVE GENETIC ALGORITHM FOR REGRESSION TESTING REDUCTION

Regression Testing is type of testing which is used to cut off the directly price associated with testing of different modules. Generally regression testing performs on test cases so that the resource utilization should be very low. Test cases in it are challenging task to achieve and suitable test cases for regression testing are difficult to judge and process. Optimization of various testing processes is done by optimization algorithms such as Genetic and Ant colony which usually provide solution to the good regression testing. Still these algorithms lack of some features which are required for better optimization of test cases in regression testing. The regression testing is the most expensive phase of the software testing, regression testing reduction eliminates the redundant test cases in the regression testing suite and saves the cost of the regression testing. In our proposed work, we will focus on optimization of regression testing with multi-objective genetic algorithm which will cover parameters like simplicity and complexity for test cases for regression testing. The complexity and simplicity for test cases will be judged and according to a common fitness function threshold we will proceed with optimization of the regression testing phases. Finally the paper evaluates the basic genetic algorithm for optimizing the test cases based on execution time; implement the multi-objective genetic algorithm with simplicity and complexity of the test cases along with execution time for test case prioritization for regression testing