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Tue 11 Oct 2022 10:50 - 11:10 at Gold A - Technical Session 4 - Mobile Apps I Chair(s): Jacques Klein

Apps’ pervasive role in our society led to the definition of test automation approaches to ensure their dependability. However, state-of-the-art approaches tend to generate large numbers of test inputs and are unlikely to achieve more than 50% method coverage.

In this article, we propose a strategy to achieve significantly higher coverage of the code affected by updates with a much smaller number of test inputs, thus alleviating the test oracle problem.

More specifically, we present ATUA, a model-based approach that synthesizes App models with static analysis, integrates a dynamically refined state abstraction function and combines complementary testing strategies, including (1) coverage of the model structure, (2) coverage of the App code, (3) random exploration, and (4) coverage of dependencies identified through information retrieval. Its model-based strategy enables ATUA to generate a small set of inputs that exercise only the code affected by the updates. In turn, this makes common test oracle solutions more cost-effective, as they tend to involve human effort.

A large empirical evaluation, conducted with 72 App versions belonging to nine popular Android Apps, has shown that ATUA is more effective and less effort-intensive than state-of-the-art approaches when testing App updates.

Tue 11 Oct

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10:30 - 12:30
Technical Session 4 - Mobile Apps IResearch Papers / NIER Track / Industry Showcase / Journal-first Papers / Tool Demonstrations at Gold A
Chair(s): Jacques Klein University of Luxembourg
Research paper
Mining Android API Usage to Generate Unit Test Cases for Pinpointing Compatibility Issues
Research Papers
Xiaoyu Sun Monash University, Xiao Chen Monash University, Yanjie Zhao Monash University, Pei Liu Monash University, John Grundy Monash University, Li Li Monash University
DOI Pre-print
Automated, Cost-effective, and Update-driven App TestingVirtual
Journal-first Papers
Chanh-Duc Ngo University of Luxembourg, Fabrizio Pastore University of Luxembourg, Lionel Briand University of Luxembourg; University of Ottawa
Link to publication
Industry talk
Fastbot2: Reusable Automated Model-based GUI Testing for Android Enhanced by Reinforcement LearningVirtual
Industry Showcase
Zhengwei Lv ByteDance, Chao Peng ByteDance, China, Zhao Zhang Bytedance Network Technology, Ting Su East China Normal University, Kai Liu Bytedance, Ping Yang Bytedance Network Technology
Vision and Emerging Results
Right to Know, Right to Refuse: Towards UI Perception-Based Automated Fine-Grained Permission Controls for Android AppsVirtual
NIER Track
Vikas K. Malviya Singapore Management University, Chee Wei Leow Singapore Management University, Ashok Kasthuri Singapore Management University, Yan Naing Tun Singapore Management University, Lwin Khin Shar Singapore Management University, Lingxiao Jiang Singapore Management University
Pre-print Media Attached
Research paper
MalWhiteout: Reducing Label Errors in Android Malware DetectionVirtual
Research Papers
Liu Wang Beijing University of Posts and Telecommunications, Haoyu Wang Huazhong University of Science and Technology, China, Xiapu Luo Hong Kong Polytechnic University, Yulei Sui University of Technology Sydney
AUSERA: Automated Security Vulnerability Detection for Android AppsVirtual
Tool Demonstrations
Sen Chen Tianjin University, Yuxin Zhang Tianjin University, Lingling Fan Nankai University, Jiaming Li Tianjin University, Yang Liu Nanyang Technological University
Research paper
A Comprehensive Evaluation of Android ICC Resolution TechniquesVirtual
Research Papers
Jiwei Yan Institute of Software at Chinese Academy of Sciences, China, Shixin Zhang Beijing Jiaotong University, China, Yepang Liu Southern University of Science and Technology, Xi Deng Institute of Software, Chinese Academy of Sciences, Jun Yan Institute of Software at Chinese Academy of Sciences, China, Jian Zhang Institute of Software at Chinese Academy of Sciences, China
DOI Pre-print