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

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
Times are displayed in 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 LinUniversity of California, Irvine, Reyhaneh JabbarvandUniversity of California, Irvine, Sam MalekUniversity of California, Irvine
11:00
20m
Talk
Test Migration Between Mobile Apps with Similar Functionality
Research Papers
Farnaz BehrangGeorgia Tech, Alessandro OrsoGeorgia Tech
11:20
20m
Talk
DaPanda: Detecting Aggressive Push Notification in Android Apps
Research Papers
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
11:40
20m
Talk
Automatic, highly accurate app permission recommendation
Journal First Presentations
Zhongxin LiuZhejiang University, Xin XiaMonash University, David LoSingapore Management University, John GrundyMonash University
Link to publication
12:00
10m
Demonstration
LIRAT: Layout and Image Recognition Driving Automated Mobile Testing of Cross-Platform
Demonstrations
Shengcheng YuNanjing University, China, Chunrong FangNanjing University, Yang FengUniversity of California, Irvine, Wenyuan ZhaoNanjing University, Zhenyu ChenNanjing University
File Attached
12:10
10m
Demonstration
Humanoid: A Deep Learning-based Approach to Automated Black-box Android App Testing
Demonstrations
Yuanchun LiPeking University, Ziyue YangPeking University, Yao GuoPeking University, Xiangqun ChenPeking University

Thu 14 Nov
Times are displayed in 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 GhanbariThe University of Texas at Dallas, Lingming ZhangThe University of Texas at Dallas
10:00
40m
Demonstration
Kotless: a Serverless Framework for Kotlin
Demonstrations
Vladislav TankovJetBrains, ITMO University, Yaroslav GolubevJetBrains Research, ITMO University, Timofey BryksinJetBrains Research, Saint-Petersburg State University
10:00
40m
Demonstration
PeASS: A Tool for Identifying Performance Changes at Code Level
Demonstrations
David Georg ReicheltUniversität Leipzig, Stefan KühneUniversität Leipzig, Wilhelm HasselbringKiel University
Pre-print Media Attached File Attached
10:00
40m
Demonstration
MutAPK: Source-Codeless Mutant Generation for Android Apps
Demonstrations
Camilo Escobar-VelásquezUniversidad de los Andes, Michael Osorio-RiañoUniversidad de los Andes, Mario Linares-VásquezSystems 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 DuShanghai JiaoTong University, Junming CaoShanghai JiaoTong University, Qinyue WuShanghai JiaoTong University, Wei LiShanghai JiaoTong University, Beijun ShenSchool of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Yuting ChenShanghai Jiao Tong University
10:00
3m
Demonstration
Humanoid: A Deep Learning-based Approach to Automated Black-box Android App Testing
Demonstrations
Yuanchun LiPeking University, Ziyue YangPeking University, Yao GuoPeking University, Xiangqun ChenPeking University
10:00
40m
Demonstration
Developer Reputation Estimator (DRE)
Demonstrations
Sadika AmreenUniversity of Tennessee Knoxville, Andrey KarnauchUniversity of Tennessee Knoxville, Audris MockusUniversity of Tennessee - Knoxville
10:00
40m
Demonstration
NeuralVis: Visualizing and Interpreting Deep Learning Models
Demonstrations
Xufan ZhangState Key Laboratory for Novel Software Technology Nanjing University, Nanjing, China, Ziyue YinState Key Laboratory for Novel Software Technology Nanjing University, Nanjing, China, Yang FengUniversity of California, Irvine, Qingkai ShiHong Kong University of Science and Technology, Jia LiuState Key Laboratory for Novel Software Technology Nanjing University, Nanjing, China, Zhenyu ChenNanjing University
10:00
40m
Demonstration
Visual Analytics for Concurrent Java Executions
Demonstrations
Cyrille ArthoKTH Royal Institute of Technology, Sweden, Monali PandeKTH Royal Institute of Technology, Qiyi TangUniversity of Oxford
10:00
40m
Demonstration
Sip4J: Statically Inferring Access Permission Contracts for Parallelising Sequential Java Programs
Demonstrations
Ayesha SadiqMonash University, Li LiMonash University, Australia, Yuan-Fang LiMonash University, Ijaz AhmedUniversity of Lahore, Sea LingMonash University
10:00
40m
Demonstration
SWAN_ASSIST: Semi-Automated Detection of Code-Specific, Security-Relevant Methods
Demonstrations
Goran PiskachevFraunhofer IEM, Lisa Nguyen Quang DoGoogle, Oshando JohnsonFraunhofer IEM, Eric BoddenHeinz 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 ZhouTsinghua University, Mingzhe WangTsinghua University, Jie LiangTsinghua University, Zhe LiuNanjing University of Aeronautics and Astronautics, Chengnian SunWaterloo University, Yu JiangTsinghua University