Uso de processamento de linguagem natural na extração de casos de testes : um mapeamento sistemático

Abstract

This paper proposes a systematic literature mapping on the application of Natural Language Processing (NLP) techniques in software testing, highlighting their relevance for automating and optimizing the extraction of test cases from requirements written in natural language. As the complexity of systems increases and the demand for quality grows, traditional testing methods face significant challenges, making the pursuit of more efficient solutions imperative. The primary objective of this study is to catalog the main approaches and techniques of NLP used in the context of software testing. A comprehensive literature review will be conducted to identify gaps between current quality assurance practices and the application of NLP. Additionally, the research will analyze the challenges and limitations encountered in implementing these techniques, seeking to understand how they can be effectively integrated into testing processes. This systematic mapping aims not only to contribute to the understanding of the state of the art at the intersection of NLP and software testing but also to serve as a guide for researchers and practitioners interested in exploring these approaches. Thus, the work intends to provide a solid foundation for future research and practical applications in this field.