Don't Do That! Hunting Down Visual Design Smells in Complex UIs against Design GuidelinesTechnical Track
Thu 27 May 2021 01:35 - 01:55 at Blended Sessions Room 3 - 2.2.3. GUI Design
Just like code smells in source code, UI design has visual design smells. We study 93 don’t-do-that guidelines in Material Design, a complex design system created by Google. We find that these don’t-guidelines go far beyond UI aesthetics, and involve seven general design dimensions (layout, typography, iconography, navigation, communication, color and shape) and four component design aspects (anatomy, placement, behavior and usage). Violating these guidelines results in visual design smells in UIs (or UI design smells). In a study of 60,756 UIs of 9,286 Android apps, we find that 7,497 UIs of 2,587 apps have at least one violation of some Material Design guidelines. This reveals the lack of developer training and tool support to avoid UI design smells. To fill this gap, we design an automated UI design smell detector (UIS-Hunter) which extracts and validates multi-modal UI information (component metadata, typography, iconography, color and edge) for detecting the violation of diverse don’t-guidelines in Material Design. The detection accuracy of UIS-Hunter is high (precision=0.81, recall=0.90) on the 60,756 UIs of 9,286 apps. We build a guideline gallery with real-world UI design smells that UIS-Hunter detects for developers to learn best Material Design practices. Our user studies show that UISHunter is more effective than manual detection of UI design smells, and the UI design smells that detected by UIS-Hunter have severely negative impacts on app users.
Wed 26 MayDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
12:55 - 13:55 | 2.2.3. GUI DesignTechnical Track / Journal-First Papers at Blended Sessions Room 3 +12h Chair(s): Ignacio Panach Universidad de Valencia | ||
12:55 20mPaper | Wireframe-based UI Design Search through Image AutoencoderJournal-First Journal-First Papers Jieshan Chen Australian National University, Australia, Chunyang Chen Monash University, Zhenchang Xing Australian National University, Xin Xia Huawei Software Engineering Application Technology Lab, Liming Zhu Data61 at CSIRO, Australia / UNSW, Australia, John Grundy Monash University, Jinshui Wang Fujian University of Technology Pre-print Media Attached | ||
13:15 20mPaper | GUIGAN: Learning to Generate GUI Designs Using Generative Adversarial NetworksTechnical Track Technical Track Tianming Zhao Jilin University, Chunyang Chen Monash University, Yuanning Liu Jilin University, Xiaodong Zhu Jilin University Pre-print Media Attached | ||
13:35 20mPaper | Don't Do That! Hunting Down Visual Design Smells in Complex UIs against Design GuidelinesTechnical Track Technical Track Bo Yang Zhejiang University, Zhenchang Xing Australian National University, Xin Xia Huawei Software Engineering Application Technology Lab, Chunyang Chen Monash University, Deheng Ye Tencent AI Lab, Shanping Li Zhejiang University Pre-print Media Attached |
Thu 27 MayDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
00:55 - 01:55 | |||
00:55 20mPaper | Wireframe-based UI Design Search through Image AutoencoderJournal-First Journal-First Papers Jieshan Chen Australian National University, Australia, Chunyang Chen Monash University, Zhenchang Xing Australian National University, Xin Xia Huawei Software Engineering Application Technology Lab, Liming Zhu Data61 at CSIRO, Australia / UNSW, Australia, John Grundy Monash University, Jinshui Wang Fujian University of Technology Pre-print Media Attached | ||
01:15 20mPaper | GUIGAN: Learning to Generate GUI Designs Using Generative Adversarial NetworksTechnical Track Technical Track Tianming Zhao Jilin University, Chunyang Chen Monash University, Yuanning Liu Jilin University, Xiaodong Zhu Jilin University Pre-print Media Attached | ||
01:35 20mPaper | Don't Do That! Hunting Down Visual Design Smells in Complex UIs against Design GuidelinesTechnical Track Technical Track Bo Yang Zhejiang University, Zhenchang Xing Australian National University, Xin Xia Huawei Software Engineering Application Technology Lab, Chunyang Chen Monash University, Deheng Ye Tencent AI Lab, Shanping Li Zhejiang University Pre-print Media Attached |