GUIDE: LLM-Driven GUI Generation Decomposition for Automated Prototyping

Graphical user interface (GUI) prototyping serves as one of the most valuable techniques for enhancing the elicitation of requirements, facilitating the visualization and refinement of customer needs and closely integrating the customer into the development activities. While GUI prototyping has a positive impact on the software development process, it simultaneously demands significant effort and resources. The emergence of Large Language Models (LLMs) with their impressive code generation capabilities offers a promising approach for automating GUI prototyping. Despite their potential, there is a gap between current LLM-based prototyping solutions and traditional user-based GUI prototyping approaches which provide visual representations of the GUI prototypes and direct editing functionality. In contrast, LLMs and related generative approaches merely produce text sequences or non-editable image output, which lacks both mentioned aspects and therefore impede supporting GUI prototyping. Moreover, minor changes requested by the user typically lead to an inefficient regeneration of the entire GUI prototype when using LLMs directly. In this work, we propose GUIDE, a novel LLM-driven GUI generation decomposition approach seamlessly integrated into the popular prototyping framework Figma. Our approach initially decomposes high-level GUI descriptions into fine-granular GUI requirements, which are subsequently translated into Material Design GUI prototypes, enabling higher controllability and more efficient adaption of changes. To efficiently conduct prompting-based generation of Material Design GUI prototypes, we propose a retrieval-augmented generation (RAG) approach to integrate the component library. Our preliminary evaluation demonstrates the effectiveness of GUIDE in bridging the gap between LLM generation capabilities and traditional GUI prototyping workflows, offering a more effective and controlled user-based approach to LLM-driven GUI prototyping. Video presentation of GUIDE is available at: https://youtu.be/C9RbhMxqpTU

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Publication Details

Published
2025-04-27
DOI
https://doi.org/10.1109/icse-companion66252.2025.00010
Citations
2
Primary Topic
Model-Driven Software Engineering Techniques
Type
article
Field-Weighted Citation Impact
4.62
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article

GUIDE: LLM-Driven GUI Generation Decomposition for Automated Prototyping

Simone Paolo Ponzetto, Kristian Kolthoff, Christian Bartelt, Alexander Maedche et al.
2 citations
Model-Driven Software Engineering Techniques
4.62
article

GUIDE: LLM-Driven GUI Generation Decomposition for Automated Prototyping

Simone Paolo Ponzetto, Kristian Kolthoff, Christian Bartelt, Alexander Maedche, Felix Kretzer
article en
2 citations

Abstract

Graphical user interface (GUI) prototyping serves as one of the most valuable techniques for enhancing the elicitation of requirements, facilitating the visualization and refinement of customer needs and closely integrating the customer into the development activities. While GUI prototyping has a positive impact on the software development process, it simultaneously demands significant effort and resources. The emergence of Large Language Models (LLMs) with their impressive code generation capabilities offers a promising approach for automating GUI prototyping. Despite their potential, there is a gap between current LLM-based prototyping solutions and traditional user-based GUI prototyping approaches which provide visual representations of the GUI prototypes and direct editing functionality. In contrast, LLMs and related generative approaches merely produce text sequences or non-editable image output, which lacks both mentioned aspects and therefore impede supporting GUI prototyping. Moreover, minor changes requested by the user typically lead to an inefficient regeneration of the entire GUI prototype when using LLMs directly. In this work, we propose GUIDE, a novel LLM-driven GUI generation decomposition approach seamlessly integrated into the popular prototyping framework Figma. Our approach initially decomposes high-level GUI descriptions into fine-granular GUI requirements, which are subsequently translated into Material Design GUI prototypes, enabling higher controllability and more efficient adaption of changes. To efficiently conduct prompting-based generation of Material Design GUI prototypes, we propose a retrieval-augmented generation (RAG) approach to integrate the component library. Our preliminary evaluation demonstrates the effectiveness of GUIDE in bridging the gap between LLM generation capabilities and traditional GUI prototyping workflows, offering a more effective and controlled user-based approach to LLM-driven GUI prototyping. Video presentation of GUIDE is available at: https://youtu.be/C9RbhMxqpTU

Karlsruhe Institute of Technology (DE), University of Mannheim (DE), Clausthal University of Technology (DE)
Openalex Percentile: Top 6%
Model-Driven Software Engineering Techniques
4.62
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