A genetic algorithm for the time-aware regression testing reduction problem

After the programmer fixes the bugs and enhances the functionality of the software project, regression testing reruns the regression testing suite to ensure that the new version software projects can run smoothly and correctly. Because 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. This paper formally defines the time-aware regression testing reduction problem. It also proposes a novel genetic algorithm for the time-aware regression testing reduction problem. It defines the representation and fitness function of the genetic algorithm, it also describes the parent selection, crossover and mutation operator of the genetic algorithm. The novel algorithm not only removes redundant test cases in the regression testing suite but also minimizes the total running time of the remaining test cases. Finally, the paper evaluates the genetic algorithm using eight example programs. The experimental result illustrates the efficiency of the proposed genetic algorithm for the time-aware regression testing reduction problem.