Application of Natural Language Processing Towards Autonomous Software Testing

Abstract

The process of creating test cases from requirements written in natural language (NL) requires intensive human efforts and can be tedious, repetitive, and error-prone. Thus, many studies have attempted to automate that process by utilizing Natural Language Processing (NLP) approaches. Furthermore, with the advent of massive language models and transfer learning techniques, people have introduced various advancements in NLP-assisted software testing with promising results. More notably, in recent years, not only have researchers been engrossed in solving the above task, but many companies have also embedded the feature to translate from human language to test cases their products. This paper presents an overview of NLP-assisted solutions being used in both the literature and the software testing industry.