Leveraging Latent Natural Language Processing Techniques for User Story Management in Agile Software Development

Abstract

User story management is a critical aspect of agile software development, as it involves understanding and prioritizing the needs of stakeholders, and translating them into actionable tasks for development teams. Furthermore, the identification of new activities within products is crucial for enhancing software quality assurance, and user story management is a crucial component of agile software development and software testing. Reusing manually written test steps would be a waste of time and effort for the testers because requirements in agile software development are continually changing and eventually becoming out-dated. Therefore, developers need to implement the necessary functions and write test steps for user stories to determine the desired behaviour or desired result of the program. In an agile world, the user story is the link between the customer and the development team, as well as the main pillar on which the development team relies to understand the product requirements. Therefore, developers need to implement the necessary functions and write test steps for user stories to determine the desired behaviour or desired result of the program. Since agile testing can detect defects early in the software life cycle and deliver a high-quality product, we propose our approach to generating test cases using natural language processing to analyse the user story. Therefore, Neural Language Processing (NLP) techniques help the development team to obtain clear data and achieve customer satisfaction.