Software Test Case Generation Using Natural Language Processing (NLP): A Systematic Literature Review

Abstract

Technologies for natural language processing (NLP) are employed to assist in the analysis and comprehension of human language. Researchers are increasingly focusing on NLP techniques to automate various software development tasks, such as software testing (test case generation). However, choosing the best NLP methods to create automated test cases is never simple. As a result, we look into using NLP techniques to create test cases. We identified 13 research articles published between 2015 and 2023 for this study. As a result, to generate automated test cases, 7 NLP techniques, 2 tools, and 1 framework have been suggested. In addition, 7 NLP algorithms have been discovered in the context of test case generation. Our evaluations indicate that the identified NLP techniques are very useful for automating the generation of test cases. The successful completion of software testing processes (test case generation) therefore requires the use of this approach/technique by software developers, testers, and software engineering teams in general. This paper will be beneficial for researchers engaged in the automation of software testing. Furthermore, it will also be helpful for academic researchers and software engineers (testers) seeking insights into the state of the art in test case generation automation. The paper discusses various tools and methods proposed for test case generation automation, aiding readers in evaluating and selecting the most suitable method for automated test case generation.