  Search-based Software Engineering has been utilized for a number of software
engineering activities. One area where Search-Based Software Engineering has
seen much application is test data generation. Evolutionary testing designates
the use of metaheuristic search methods for test case generation. The search
space is the input domain of the test object, with each individual or potential
solution, being an encoded set of inputs to that test object. The fitness
function is tailored to find test data for the type of test that is being
undertaken. Evolutionary Testing (ET) uses optimizing search techniques such as
evolutionary algorithms to generate test data. The effectiveness of GA-based
testing system is compared with a Random testing system. For simple programs
both testing systems work fine, but as the complexity of the program or the
complexity of input domain grows, GA-based testing system significantly
outperforms Random testing.
