ReverseORC: Reverse Engineering of Resizable User Interface Layouts with OR-Constraints
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Abstract (arXiv)
Reverse engineering (RE) of user interfaces (UIs) plays an important role in software evolution. However, the large diversity of UI technologies and the need for UIs to be resizable make this challenging. We propose ReverseORC, a novel RE approach able to discover diverse layout types and their dynamic resizing behaviours independently of their implementation, and to specify them by using OR constraints. Unlike previous RE approaches, ReverseORC infers flexible layout constraint specifications by sampling UIs at different sizes and analyzing the differences between them. It can create specifications that replicate even some non-standard layout managers with complex dynamic layout behaviours. We demonstrate that ReverseORC works across different platforms with very different layout approaches, e.g., for GUIs as well as for the Web. Furthermore, it can be used to detect and fix problems in legacy UIs, extend UIs with enhanced layout behaviours, and support the creation of flexible UI layouts.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 2 of its 81 references that are in the map. First posted on arXiv 23 Feb 2022.
Builds on
2 of 81 references.
References · 2
Built on by
Citing papers per year: 2023: 2; 2024: 2; 2025: 2.
6 papers.
- 2023ILuvUI: Instruction-tuned LangUage-Vision modeling of UIs from Machine Conversationscited by 17
- 2024EyeFormer: Predicting Personalized Scanpaths with Transformer-Guided Reinforcement Learningcited by 8
- 2024Graph4GUI: Graph Neural Networks for Representing Graphical User Interfacescited by 6
- 2023Pairwise GUI Dataset Construction Between Android Phones and Tabletscited by 1
- 2025ControlGUI: Guiding Generative GUI Exploration through Perceptual Visual Flowcited by 0
- 2025StructLayoutFormer:Conditional Structured Layout Generation via Structure Serialization and Disentanglementcited by 0
- 2025StructLayoutFormer:Conditional Structured Layout Generation via Structure Serialization and Disentanglement30 Oct 2025
- 2025ControlGUI: Guiding Generative GUI Exploration through Perceptual Visual Flow5 Feb 2025
- 2024Graph4GUI: Graph Neural Networks for Representing Graphical User Interfaces21 Apr 2024
- 2024EyeFormer: Predicting Personalized Scanpaths with Transformer-Guided Reinforcement Learning15 Apr 2024
- 2023ILuvUI: Instruction-tuned LangUage-Vision modeling of UIs from Machine Conversations7 Oct 2023
- 2023Pairwise GUI Dataset Construction Between Android Phones and Tablets7 Oct 2023