International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Testing software is essential to ensure quality in IT systems. One of the testing methods is randomized testing which is effective for unit testing. The effectiveness of randomized testing is influenced by certain parameters. One such parameter is frequency of method calls. In this paper, the authors implement a genetic algorithm for finding parameters required by randomized testing. This will help in maximum test coverage. The problem with GA is that the representations in GA are bulky whose size and content has to be reduced. They build a tool which will reduce the representations of GA substantially. This will reduce a great deal of latency while achieving the results same as full representations of GA.