Blogs (1) >>
ASE 2019
Sun 10 - Fri 15 November 2019 San Diego, California, United States
Tue 12 Nov 2019 10:40 - 11:00 at Hillcrest - Mobile 1 Chair(s): Marouane Kessentini

GUI-based testing has been primarily used to examine the functionality and usability of mobile apps. Despite the numerous GUI-based test input generation techniques proposed in the literature, these techniques are still limited by (1) lack of context-aware text inputs; (2) failing to generate expressive tests; and (3) absence of test oracles. To address these limitations, we propose CraftDroid, a framework that leverages information retrieval, along with static and dynamic analysis techniques, to extract the human knowledge from an existing test suite for one app and transfer the test cases and oracles to be used for testing other apps with the similar functionalities. Evaluation of CraftDroid on real-world commercial Android apps corroborates its effectiveness by achieving 73% precision and 90% recall on average for transferring both the GUI events and oracles. In addition, 75% of the attempted transfers successfully generated valid and feature-based tests for popular features among apps in the same category.

Tue 12 Nov

10:40 - 12:20: Papers - Mobile 1 at Hillcrest
Chair(s): Marouane KessentiniUniversity of Michigan
ase-2019-papers10:40 - 11:00
Test Transfer Across Mobile Apps Through Semantic Mapping
Jun-Wei LinUniversity of California, Irvine, Reyhaneh JabbarvandUniversity of California, Irvine, Sam MalekUniversity of California, Irvine
ase-2019-papers11:00 - 11:20
Test Migration Between Mobile Apps with Similar Functionality
Farnaz BehrangGeorgia Tech, Alessandro OrsoGeorgia Tech
ase-2019-papers11:20 - 11:40
DaPanda: Detecting Aggressive Push Notification in Android Apps
Tianming LiuBeijing University of Posts and Telecommunications, China, Haoyu WangBeijing University of Posts and Telecommunications, China, Li LiMonash University, Australia, Guangdong BaiGriffith University, Yao GuoPeking University, Guoai Xu Beijing University of Posts and Telecommunications
ase-2019-Journal-First-Presentations11:40 - 12:00
Automatic, highly accurate app permission recommendation
Zhongxin LiuZhejiang University, Xin XiaMonash University, David LoSingapore Management University, John GrundyMonash University
Link to publication
ase-2019-Demonstrations12:00 - 12:10
LIRAT: Layout and Image Recognition Driving Automated Mobile Testing of Cross-Platform
Shengcheng YuNanjing University, China, Chunrong FangNanjing University, Yang FengUniversity of California, Irvine, Wenyuan ZhaoNanjing University, Zhenyu ChenNanjing University
ase-2019-Demonstrations12:10 - 12:20
Humanoid: A Deep Learning-based Approach to Automated Black-box Android App Testing
Yuanchun LiPeking University, Ziyue YangPeking University, Yao GuoPeking University, Xiangqun ChenPeking University