| Summary: | User Stories are commonly used artifacts to capture user requirements in agile software development. They are short, semi-structured statements that describe requirements. Natural Language Processing (NLP) techniques can be advantageous for research on user stories. This paper investigates User Stories and NLP about their applications, critically examines existing research approaches related to NLP in user stories and presents the challenges and suggested future work. Relevant papers were obtained from well-recognized digital libraries and scientific databases, including ScienceDirect, Scopus, SpringerLink, and IEEE Xplore. Inclusion and exclusion criteria were applied to filter search results and obtain comprehensive findings. The search results identified 1175 papers published between January 2014 and January 2024. After applying the inclusion/exclusion criteria, 35 primary studies discussing NLP techniques in user stories were selected. The purposes of these studies vary, encompassing defect discovery, software artifact generation, key abstraction identification in user stories, and linking models and user stories. NLP can assist system analysts in managing user stories. Implementing NLP in user stories offers numerous opportunities and challenges. Exploring NLP techniques and employing rigorous evaluation methods are necessary for high-quality research. As with general NLP research, understanding the context of sentences remains a challenge.
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