Automatic goal-oriented test data generation using a Genetic algorithm and simulated annealing

The literature on automatic test case generation has significantly arguments its importance in software testing. The solution to this un-decidable problem can reduce the financial resources spent in testing a software system. In this paper Evolutionary Genetic algorithm and simulated annealing based approach for automatic test case generation is presented. The fitness of target goal is achieved by instrumenting the program using branch distance approach and the generated test cases using genetic algorithm and simulated annealing are evaluated and compared in terms of 1) number of generation needed to reach to the target goal and 2) The time taken to generate test cases.