Automatic test data generation for program paths using genetic algorithms

A new technique and tool are presented for test data generation for path testing. They are based on the dynamic technique and on a Genetic Algorithm, which evolves a population of input data towards reaching and solving the predicates along the program paths. We improve the performance of test data generation by using past input data to compose the initial population for the search. An experiment was done to assess the performance of the techniques compared to that of random data generation.