Blogs (1) >>
ASE 2019
Sun 10 - Fri 15 November 2019 San Diego, California, United States
Tue 12 Nov 2019 12:10 - 12:20 at Hillcrest - Mobile 1 Chair(s): Marouane Kessentini
Thu 14 Nov 2019 10:00 - 10:03 at Kensington Ballroom - Poster Session: Tool Demonstrations 3

Automated input generators must constantly choose which UI element to interact with and how to interact with it, in order to achieve high coverage with a limited time budget. Currently, most black-box input generators adopt pseudo-random or brute-force searching strategies, which may take very long to find the correct combination of inputs that can drive the app into new and important states. We propose Humanoid, a deep learning-based approach to automated black-box Android app testing, which can explore the app more efficiently. The key technique behind Humanoid is a deep neural network model that can learn how human users choose actions based on an app’s GUI from human interaction traces . The learned model can be used to guide test input generation to achieve higher coverage. Experiments on both open-source apps and market apps demonstrate that Humanoid is able to reach higher coverage, and faster as well, than the state-of-the-art test input generators. Humanoid is open-sourced at https://github.com/yzygitzh/Humanoid and a demo video can be found at https://youtu.be/PDRxDrkyORs.

Tue 12 Nov

Displayed time zone: Tijuana, Baja California change

10:40 - 12:20
10:40
20m
Talk
Test Transfer Across Mobile Apps Through Semantic Mapping
Research Papers
Jun-Wei Lin University of California, Irvine, Reyhaneh Jabbarvand University of California, Irvine, Sam Malek University of California, Irvine
11:00
20m
Talk
Test Migration Between Mobile Apps with Similar Functionality
Research Papers
Farnaz Behrang Georgia Tech, Alessandro Orso Georgia Tech
11:20
20m
Talk
DaPanda: Detecting Aggressive Push Notification in Android Apps
Research Papers
Tianming Liu Beijing University of Posts and Telecommunications, China, Haoyu Wang Beijing University of Posts and Telecommunications, China, Li Li Monash University, Australia, Guangdong Bai Griffith University, Yao Guo Peking University, Guoai Xu Beijing University of Posts and Telecommunications
11:40
20m
Talk
Automatic, highly accurate app permission recommendation
Journal First Presentations
Zhongxin Liu Zhejiang University, Xin Xia Monash University, David Lo Singapore Management University, John Grundy Monash University
Link to publication
12:00
10m
Demonstration
LIRAT: Layout and Image Recognition Driving Automated Mobile Testing of Cross-Platform
Demonstrations
Shengcheng Yu Nanjing University, China, Chunrong Fang Nanjing University, Yang Feng University of California, Irvine, Wenyuan Zhao Nanjing University, Zhenyu Chen Nanjing University
File Attached
12:10
10m
Demonstration
Humanoid: A Deep Learning-based Approach to Automated Black-box Android App Testing
Demonstrations
Yuanchun Li Peking University, Ziyue Yang Peking University, Yao Guo Peking University, Xiangqun Chen Peking University

Thu 14 Nov

Displayed time zone: Tijuana, Baja California change

10:00 - 10:40
Poster Session: Tool Demonstrations 3Demonstrations at Kensington Ballroom
10:00
40m
Demonstration
PraPR: Practical Program Repair via Bytecode Mutation
Demonstrations
Ali Ghanbari Iowa State University, Lingming Zhang The University of Texas at Dallas
10:00
40m
Demonstration
Kotless: a Serverless Framework for Kotlin
Demonstrations
Vladislav Tankov JetBrains, ITMO University, Yaroslav Golubev JetBrains Research, Timofey Bryksin JetBrains Research, Saint-Petersburg State University
10:00
40m
Demonstration
PeASS: A Tool for Identifying Performance Changes at Code Level
Demonstrations
David Georg Reichelt Universität Leipzig, Stefan Kühne Universität Leipzig, Wilhelm Hasselbring Kiel University
Pre-print Media Attached File Attached
10:00
40m
Demonstration
MutAPK: Source-Codeless Mutant Generation for Android Apps
Demonstrations
Camilo Escobar-Velásquez Universidad de los Andes, Michael Osorio-Riaño Universidad de los Andes, Mario Linares-Vásquez Systems and Computing Engineering Department , Universidad de los Andes , Bogotá, Colombia
10:00
40m
Demonstration
CocoQa: Question Answering for Coding Conventions over Knowledge Graphs
Demonstrations
Tianjiao Du Shanghai JiaoTong University, Junming Cao Shanghai JiaoTong University, Qinyue Wu Shanghai JiaoTong University, Wei Li Shanghai JiaoTong University, Beijun Shen School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Yuting Chen Shanghai Jiao Tong University
10:00
3m
Demonstration
Humanoid: A Deep Learning-based Approach to Automated Black-box Android App Testing
Demonstrations
Yuanchun Li Peking University, Ziyue Yang Peking University, Yao Guo Peking University, Xiangqun Chen Peking University
10:00
40m
Demonstration
Developer Reputation Estimator (DRE)
Demonstrations
Sadika Amreen University of Tennessee Knoxville, Andrey Karnauch University of Tennessee Knoxville, Audris Mockus University of Tennessee - Knoxville
10:00
40m
Demonstration
NeuralVis: Visualizing and Interpreting Deep Learning Models
Demonstrations
Xufan Zhang State Key Laboratory for Novel Software Technology Nanjing University, Nanjing, China, Ziyue Yin State Key Laboratory for Novel Software Technology Nanjing University, Nanjing, China, Yang Feng University of California, Irvine, Qingkai Shi Hong Kong University of Science and Technology, Jia Liu State Key Laboratory for Novel Software Technology Nanjing University, Nanjing, China, Zhenyu Chen Nanjing University
10:00
40m
Demonstration
Visual Analytics for Concurrent Java Executions
Demonstrations
Cyrille Artho KTH Royal Institute of Technology, Sweden, Monali Pande KTH Royal Institute of Technology, Qiyi Tang University of Oxford
10:00
40m
Demonstration
Sip4J: Statically Inferring Access Permission Contracts for Parallelising Sequential Java Programs
Demonstrations
Ayesha Sadiq Monash University, Li Li Monash University, Australia, Yuan-Fang Li Monash University, Ijaz Ahmed University of Lahore, Sea Ling Monash University
10:00
40m
Demonstration
SWAN_ASSIST: Semi-Automated Detection of Code-Specific, Security-Relevant Methods
Demonstrations
Goran Piskachev Fraunhofer IEM, Lisa Nguyen Quang Do Google, Oshando Johnson Fraunhofer IEM, Eric Bodden Heinz Nixdorf Institut, Paderborn University and Fraunhofer IEM
Pre-print Media Attached File Attached
10:00
40m
Demonstration
VisFuzz: Understanding and Intervening Fuzzing with Interactive Visualization
Demonstrations
Chijin Zhou Tsinghua University, Mingzhe Wang Tsinghua University, Jie Liang Tsinghua University, Zhe Liu Nanjing University of Aeronautics and Astronautics, Chengnian Sun Waterloo University, Yu Jiang Tsinghua University