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Robust relational layout synthesis from examples for Android

Authors:

Martin VechevAuthors Info & Claims

Proceedings of the ACM on Programming Languages, Volume 2, Issue OOPSLA

Article No.: 156, Pages 1 - 29

https://doi.org/10.1145/3276526

Published: 24 October 2018 Publication History

Abstract

We present a novel approach for synthesizing robust relational layouts from examples. Given an application design consisting of a set of views and their location on the screen, we synthesize a relational layout that when rendered, places the components at that same location.

We present an end-to-end system, called InferUI, that addresses the above challenge in the context of Android. The system is based on the following technical contributions: (i) a formalization of the latest and most efficient ConstraintLayout class, capturing a rich set of relational constraints, (ii) a set of robustness properties designed to prevent common layout generalization errors, (iii) a synthesis algorithm that produces relational layouts that generalize across multiple screen sizes and resolutions, and (iv) a probabilistic model of constraints that guides the synthesizer towards layouts preferred by developers.

Our evaluation shows that InferUI is practically effective: it successfully synthesizes real world complex layouts obtained from top 500 GitHub and top 500 Google Play Store applications, succeeds in 100% of the cases when synthesizing layouts for a single device, and correctly generalizes 92% of the views across multiple devices, all without requiring additional specifications.

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Cited By

Wu JTodi KChan JMyers BLafreniere B(2024)FrameKit: A Tool for Authoring Adaptive UIs Using KeyframesProceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645176(660-674)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3640543.3645176
Jiang YLu YKnearem TKliman-Silver CLutteroth CLi TNichols JStuerzlinger W(2024)Computational Methodologies for Understanding, Automating, and Evaluating User InterfacesExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3636316(1-7)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613905.3636316
Jiang YZhou CGarg VOulasvirta A(2024)Graph4GUI: Graph Neural Networks for Representing Graphical User InterfacesProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642822(1-18)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642822
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Robust relational layout synthesis from examples for Android

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Published In

cover image Proceedings of the ACM on Programming Languages

Proceedings of the ACM on Programming Languages Volume 2, Issue OOPSLA

November 2018

1656 pages

EISSN:2475-1421

DOI:10.1145/3288538

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Copyright © 2018 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 October 2018

Published in PACMPL Volume 2, Issue OOPSLA

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Cited By

Wu JTodi KChan JMyers BLafreniere B(2024)FrameKit: A Tool for Authoring Adaptive UIs Using KeyframesProceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645176(660-674)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3640543.3645176
Jiang YLu YKnearem TKliman-Silver CLutteroth CLi TNichols JStuerzlinger W(2024)Computational Methodologies for Understanding, Automating, and Evaluating User InterfacesExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3636316(1-7)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613905.3636316
Jiang YZhou CGarg VOulasvirta A(2024)Graph4GUI: Graph Neural Networks for Representing Graphical User InterfacesProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642822(1-18)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642822
Xiao SChen YSong YChen LSun LZhen YChang YZhou T(2024)UI semantic component group detection: Grouping UI elements with similar semantics in mobile graphical user interfaceDisplays10.1016/j.displa.2024.10267983(102679)Online publication date: Jul-2024
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Jiang YLu YLutteroth CLi TNichols JStuerzlinger W(2023)The Future of Computational Approaches for Understanding and Adapting User InterfacesExtended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544549.3573805(1-5)Online publication date: 19-Apr-2023
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ÖZÇEVİK Y(2022)Geleneksel İç İçe Yerleşimler ve Kısıt Yerleşimi İçeren Melez Android Ön Yüz Geliştirme YaklaşımıA Hybrid Android Frontend Development Approach with Traditional Nesting Layouts and Constraint LayoutInternational Journal of Innovative Engineering Applications10.46460/ijiea.11162226:2(245-254)Online publication date: 30-Dec-2022
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Su YChen CWang JLiu ZWang DLi SWang Q(2022)The Metamorphosis: Automatic Detection of Scaling Issues for Mobile AppsProceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering10.1145/3551349.3556935(1-12)Online publication date: 10-Oct-2022
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Xie MXing ZFeng SXu XZhu LChen CRoychoudhury ACadar CKim M(2022)Psychologically-inspired, unsupervised inference of perceptual groups of GUI widgets from GUI imagesProceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3540250.3549138(332-343)Online publication date: 7-Nov-2022
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