User Story Based Automated Test Case Generation Using NLP

The progress of technology requires software systems to be of higher quality in order to meet the increasing complexity and frequency of changing needs. The present software development life cycle prioritizes the adjustment to evolving client requirements across the different stages of project development, facilitated by Continuous Integration and Continuous Deployment. The process produces a substantial volume of data that can serve as a valuable resource for automating test case production and reducing the need for manual intervention. This publication presents a suggested technique that utilizes natural language processing to automate the generation of test cases, hence minimizing the need for human involvement. The proposed approach has three phases: input-output categorization utilizing sentiment analysis, production of regular expressions, and generation of test cases. The main contribution of this article involves the classification of user keywords and the construction of test cases using them. The suggested model generates diverse outputs to create both positive and negative test cases. It has been tested with 700 user stories that have varying levels of abstraction in articulating the requirements.