Write a Blog >>
ICSE 2020
Wed 24 June - Thu 16 July 2020
Thu 9 Jul 2020 00:00 - 00:12 at Goguryeo - P14-Testing Chair(s): Shin Yoo

GUI animations, such as card movement, menu slide in/out, snackbar display, provide appealing user experience and enhance the usability of mobile applications. These GUI animations should not violate the platform’s UI design guidelines (referred to as design-don’t guideline in this work) regarding component motion and interaction, content appearing and disappearing, and elevation and shadow changes.However, none of existing static code analysis, functional GUI testing and GUI image comparison techniques can see'' the GUI animations on the scree, and thus they cannot support the linting of GUI animations against design-don't guidelines. In this work, we formulate this GUI animation linting problem as a multi-class screencast classification task, but we do not have sufficient labeled GUI animations to train the classifier. Instead, we propose an unsupervised, computer-vision based adversarial autoencoder to solve this linting problem. Our autoencoder learns to group similar GUI animations byseeing'' lots of unlabeled real-application GUI animations and learning to generate them. As the first work of its kind, we build the datasets of synthetic and real-world GUI animations. Through experiments on these datasets, we systematically investigate the learning capability of our model and its effectiveness and practicality for linting GUI animations, and identify the challenges in this linting problem for future work.

Conference Day
Thu 9 Jul

Displayed time zone: (UTC) Coordinated Universal Time change

00:00 - 01:00
P14-TestingTechnical Papers / Software Engineering in Practice at Goguryeo
Chair(s): Shin YooKorea Advanced Institute of Science and Technology
00:00
12m
Talk
Seenomaly: Vision-Based Linting of GUI Animation Effects Against Design-Don’t GuidelinesTechnical
Technical Papers
Dehai ZhaoAustralian National University, Zhenchang XingAustralia National University, Chunyang ChenMonash University, Xiwei XuData 61, Liming ZhuCSIRO's Data61 and UNSW, Guoqiang LiShanghai Jiao Tong University, Jinshui WangSchool of Information Science and Engineering, Fujian University of Technology, Fuzhou, China
00:12
12m
Talk
Fuzz Testing based Data Augmentation to Improve Robustness of Deep Neural NetworksTechnical
Technical Papers
Xiang GaoNational University of Singapore, Singapore, Ripon SahaFujitsu Laboratories of America, Inc., Mukul R. PrasadFujitsu Laboratories of America, Inc, Abhik RoychoudhuryNational University of Singapore, Singapore
00:24
12m
Talk
Modeling and Ranking Flaky Tests at AppleSEIP
Software Engineering in Practice
Emily KowalczykApple Inc., Karan NairApple, Zebao GaoApple, Leopold SilbersteinApple Inc., Teng LongApple, Atif MemonApple Inc.
00:36
12m
Talk
Testing File System Implementations on Layered ModelsTechnicalArtifact Available
Technical Papers
Dongjie ChenNanjing University, Yanyan JiangNanjing University, Chang XuNanjing University, Xiaoxing MaNanjing University, Jian LuNanjing University
00:48
12m
Talk
A Cost-efficient Approach to Building in Continuous IntegrationTechnical
Technical Papers
Xianhao JinVirginia Tech, USA, Francisco ServantVirginia Tech
Pre-print