An evolutionary testing approach for test data generation from EFSM model with string data input

摘要

The thesis has aimed to test data generation from EFSM model with string data input. Intesting area a very few work is done to generate test data with string data input. So this topicis interesting to the testing arena. To reach the goal a genetic algorithm (GA) tool isdeveloped. A study was carried out to choose the best fitness function for string data input;resulting modified edit distance algorithm was used as a fitness function. Firstly, string andalphanumeric values with different lengths were passed through the GA tool and evaluated theresult. Then three EFSM models were designed and deployed to the GA tool where most ofcases the whole path is passed. This work was limited to string equality and there is a scopeto work with string ordering in future.