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Extracting conceptual models from user stories with Visual Narrator

Extracting conceptual models from user stories with Visual Narrator Extracting conceptual models from natural language requirements can help identify dependencies, redundancies, and conflicts between requirements via a holistic and easy-to-understand view that is generated from lengthy textual specifications. Unfortunately, existing approaches never gained traction in practice, because they either require substantial human involvement or they deliver too low accuracy. In this paper, we propose an automated approach called Visual Narrator based on natural language processing that extracts conceptual models from user story requirements. We choose this notation because of its popularity among (agile) practitioners and its focus on the essential components of a requirement: Who? What? Why? Coupled with a careful selection and tuning of heuristics, we show how Visual Narrator enables generating conceptual models from user stories with high accuracy. Visual Narrator is part of the holistic Grimm method for user story collaboration that ranges from elicitation to the interactive visualization and analysis of requirements. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Requirements Engineering Springer Journals

Extracting conceptual models from user stories with Visual Narrator

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References (75)

Publisher
Springer Journals
Copyright
Copyright © 2017 by The Author(s)
Subject
Computer Science; Software Engineering
ISSN
0947-3602
eISSN
1432-010X
DOI
10.1007/s00766-017-0270-1
Publisher site
See Article on Publisher Site

Abstract

Extracting conceptual models from natural language requirements can help identify dependencies, redundancies, and conflicts between requirements via a holistic and easy-to-understand view that is generated from lengthy textual specifications. Unfortunately, existing approaches never gained traction in practice, because they either require substantial human involvement or they deliver too low accuracy. In this paper, we propose an automated approach called Visual Narrator based on natural language processing that extracts conceptual models from user story requirements. We choose this notation because of its popularity among (agile) practitioners and its focus on the essential components of a requirement: Who? What? Why? Coupled with a careful selection and tuning of heuristics, we show how Visual Narrator enables generating conceptual models from user stories with high accuracy. Visual Narrator is part of the holistic Grimm method for user story collaboration that ranges from elicitation to the interactive visualization and analysis of requirements.

Journal

Requirements EngineeringSpringer Journals

Published: May 20, 2017

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