Automatic generation of graphical user interface prototypes from unrestricted natural language requirements


Kolthoff, Kristian



DOI: https://doi.org/10.1109/ASE.2019.00148
URL: https://ieeexplore.ieee.org/document/8952477
Additional URL: https://2019.ase-conferences.org/details/ase-2019-...
Document Type: Conference or workshop publication
Year of publication: 2020
Book title: 2019 34th IEEE/ACM International Conference on Automated Software Engineering : 10-15 November 2019 : San Diego, California : proceedings
Page range: 1234-1237
Conference title: ASE 2019
Location of the conference venue: San Diego, CA
Date of the conference: 11.-15.11.2019
Publisher: Zimmermann, Thomas
Place of publication: Piscataway, NJ
Publishing house: IEEE
ISBN: 978-1-7281-2509-1 , 978-1-7281-2508-4
ISSN: 1938-4300 , 2643-1572
Publication language: English
Institution: Außerfakultäre Einrichtungen > Institut für Enterprise Systems (InES)
Subject: 004 Computer science, internet
Abstract: High-fidelity GUI prototyping provides a meaningful manner for illustrating the developers’ understanding of the requirements formulated by the customer and can be used for productive discussions and clarification of requirements and expectations. However, high-fidelity prototypes are time-consuming and expensive to develop. Furthermore, the interpretation of requirements expressed in informal natural language is often error-prone due to ambiguities and misunderstandings. In this dissertation project, we will develop a methodology based on Natural Language Processing (NLP) for supporting GUI prototyping by automatically translating Natural Language Requirements (NLR) into a formal Domain-Specific Language (DSL) describing the GUI and its navigational schema. The generated DSL can be further translated into corresponding target platform prototypes and directly provided to the user for inspection. Most related systems stop after generating artifacts, however, we introduce an intelligent and automatic interaction mechanism that allows users to provide natural language feedback on generated prototypes in an iterative fashion, which accordingly will be translated into respective prototype changes.




Dieser Eintrag ist Teil der Universitätsbibliographie.




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