Priorização de casos de teste utilizando redes neurais artificiais

Abstract

Software testing is one of the most arduous steps in software systems development. For the product to present the expected quality, several test cases are executed. A single requirement can generate a large amount of test cases, and due to this high number, the manual test often becomes very costly to the software development, making it essential to prioritize those test cases where there is a greater possibility of occurrence incidence of failures. This work presents a way to automate the prioritization of test cases using artificial neural networks.