Proceedings of the 33rd International Conference on Software Engineering
Proceedings of the 2012 International Symposium on Software Testing and Analysis
Information Sciences: an International Journal
The optimisation of stochastic grammars to enable cost-effective probabilistic structural testing
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Testing techniques selection based on ODC fault types and software metrics
Journal of Systems and Software
Search methodologies in real-world software engineering
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Using automated program repair for evaluating the effectiveness of fault localization techniques
Proceedings of the 2013 International Symposium on Software Testing and Analysis
| Hi-index | 0.05 |
Statistical testing has been shown to be more efficient at detecting faults in software than other methods of dynamic testing such as random and structural testing. Test data are generated by sampling from a probability distribution chosen so that each element of the software's structure is exercised with a high probability. However, deriving a suitable distribution is difficult for all but the simplest of programs. This paper demonstrates that automated search is a practical method of finding near-optimal probability distributions for real-world programs, and that test sets generated from these distributions continue to show superior efficiency in detecting faults in the software.