Black Box Testing is immensely important because the source code of a module is not always available. Enterprise Resource Planning systems are also tested using Black Box Testing wherein all the test cases are not equally important. The prioritization of these test cases would be helpful in case of premature termination of testing, due to lack of resources. This paper proposes a Neural Network based method to prioritize test cases. The paper also presents guidelines for prioritizing test cases. The technique has been tested using a financial management system and the results are encouraging. This paper paves way for applying Neural Network in Black Box Testing and presents a framework, which would help both researchers and practitioners.
['Harsh Bhasin', 'Esha Khanna']
Neural network based black box testing