Application of Big Bang Big Crunch Algorithm to Software Testing
This paper presents a Big Bang Big Crunch concept based search algorithm for automatic generation of structural software tests. Test cases are symbolically generated by measuring fitness of individuals with the help of branch distance based objective function. Evaluation of the test generator was performed using ten real world programs. Some of these programs had large ranges for input variables. Results show that the new technique is a reasonable alternative for test data generation, but doesn't perform very well for large inputs and where constraints are having many equality constraints.