Identification of potentially infeasible program paths by monitoring the search for test data

A tool and techniques are presented for test data generation and identification of a path´s likely unfeasibility in structural software testing. The tool is based on the dynamic technique and search using genetic algorithms. Our work introduces a new fitness function that combines control and data flow dynamic information to improve the process of search for test data. The unfeasibility issue is addressed by monitoring the genetic algorithm´s search progress. An experiment shows the validity of the developed solutions and the benefit of using the tool