Dynamic localisation and automatic correction of software faults using evolutionary mutation testing

Software testing has recently turned to more sophisticated techniques, like automatic, self-adaptive mutation testing, aiming at improving the effectiveness of the testing process and handling the associated complexity that increases the level of time and effort spent. Mutation testing refers to the application of mutation operators on correctly functioning programs so as to induce common programming errors and then assess the ability of a set of test cases to reveal them. In the above context the present paper introduces a novel methodology for identifying and correcting faults in Java source code using dynamic slicing coupled with mutation testing and enhanced by Genetic Algorithms. A series of experiments was conducted to assess the effectiveness of the proposed approach, using different types of errors and sample programs. The results were quite encouraging as regards the ability of the approach to localise the faults, as well as to suggest the appropriate correction(s) to eliminate them