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90% of agile practitioners employ user stories for capturing requirements. Of these, 70% follow a simple template when creating user stories: As a I want to , so that . User stories' popularity among practitioners and their simple yet strict structure make them ideal candidates for automatic reasoning based on natural language processing. In our research, we have found that circa 50% of real-world user stories contain easily preventable errors that may endanger their potential. To alleviate this problem, we have created methods, theories and tools that support creating better user stories. This tutorial combines our previous work into a pipeline for working with user stories: (1) The basics of creating user stories, and their use in requirements engineering; (2) How to improve user story quality with the Quality User Story Framework and AQUSA tool; and (3) How to generate conceptual models from user stories using the Visual Narrator and the Interactive Narrator tools. Our toolset is demonstrated with results obtained from 20+ software companies employing user stories.
Dalpiaz et al. (Wed,) studied this question.
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