Agile Requirements Engineering with User Stories

90% of agile practitioners employ user stories for capturing requirements. 70% of these practitioners follow a simple template when creating user stories: As a (role), I want to (action), [so that (benefit)]. User stories' popularity 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 diminsh 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 tool-supported pipeline for working with user stories. After presenting the basics of creating user stories, we explain (1) how to improve user story quality by identifying and resolving quality defects; (2) how to generate conceptual models from user stories; and (3) how to cope with terminological ambiguity and incompleteness. Our toolset is demonstrated with results obtained from 20+ software companies that employ user stories.