Gallery D.C.: Auto-created GUI Component Gallery for Design Search and Knowledge Discovery
April 14, 2022 Β· Declared Dead Β· π 2022 IEEE/ACM 44th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)
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Authors
Sidong Feng, Chunyang Chen, Zhenchang Xing
arXiv ID
2204.06700
Category
cs.SE: Software Engineering
Cross-listed
cs.HC
Citations
12
Venue
2022 IEEE/ACM 44th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)
Last Checked
3 months ago
Abstract
GUI design is an integral part of software development. The process of designing a mobile application typically starts with the ideation and inspiration search from existing designs. However, existing information-retrieval based, and database-query based methods cannot efficiently gain inspirations in three requirements: design practicality, design granularity and design knowledge discovery. In this paper we propose a web application, called \tool that aims to facilitate the process of user interface design through real world GUI component search. Gallery D.C. indexes GUI component designs using reverse engineering and deep learning based computer vision techniques on millions of real world applications. To perform an advanced design search and knowledge discovery, our approach extracts information about size, color, component type, and text information to help designers explore multi-faceted design space and distill higher-order of design knowledge. Gallery D.C. is well received via an informal evaluation with 7 professional designers. Web Link: http://mui-collection.herokuapp.com/. Demo Video Link: https://youtu.be/zVmsz_wY5OQ.
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