Automatic Recognition and Segmentation of Composite User Stories Based on Semantic Analysis

User stories are often used in agile development to express user needs. Accurate and rapid understanding of user stories is critical to product development. One of the major obstacles to accurate and efficient story understanding is the ambiguity of story statement caused by the existence of compound user stories. Therefore, the understanding of user stories is crucial to product development. One aspect that hinders the efficiency of story understanding is compound user stories, especially in Chinese, so identifying compound stories in the early stages of development is a major goal of this article. This paper proposes a method for identifying and segmenting compound stories based on semantic analysis, which includes analyzing the structural and semantic features of compound stories, building a feature dictionary, and automatically recognizing compound stories based on HanLP. This paper takes the user story of a game live broadcast system as an example, and the research proves that the method proposed in this paper can well identify common compound user stories.