I am an assistant to special researcher (assistant scientist) at the Institute of Software Chinese Academy of Sciences, University of Chinese Academy of Sciences, China. I obtained my PhD from University of Chinese Academy of Sciences (UCAS), China. I received the ACM Student Research Competition (SRC) 2023 Grand Finals Winners, 1st Place, Graduate Category, in 2023. (The first doctoral student in Chinese Mainland to win the honor.) My research focuses on Software Engineering, Mobile Testing, Deep Learning and Human-Computer Interaction. Specifically, I apply AI and light-weight program analysis technology in the following directions:

AI(LLM)-assisted automated mobile app development including requirement elicitation app GUI testing [ICSE’23a, ICSE’23b, ICSE’24a, ICSE’24b], usability [ASE’20, FSE’21, TSE’22, ASE’22], and bug replay [ICSE’23, ICSE’24].

Human machine collaborative testing including testing guide for testers [CHI’24, CHI’22, ICSE’22].

AI-empowered mining software repository including issue report mining [ESEM’20, ESEM’21].

My research interest includes Software Engineering and Human Machine Interaction. I have published 15 papers at the top international Software Engineering and Human Machine Interaction conferences/journal (CCF-A) with total google scholar citations 616.

🔥 News

2024.09: 🎉🎉 I received the “Doctoral Dissertation Incentive Program of the Software Engineering Professional Committee of the CCF”.
2024.08: 🎉🎉 I received the “Excellent Doctoral Dissertation of Chinese Academy of Sciences in 2024”.
2024.05: 🎉🎉 The paper received the “Best　Paper　Honourable　Mention” in CHI’24.
2024.01: 🎉🎉 A full research paper is accepted at Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems (CHI’24).
2023.10: 🎉🎉 Three full research papers are accepted at International Conference on Software Engineering (ICSE’24).
2023.05: 🎉🎉 I received the ACM Student Research Competition (SRC) 2023 Grand Finals Winners, 1st Place, Graduate Category. (The first doctoral student in Chinese Mainland to win the honor.)
2023.05: 🎉🎉 I received the “President of Chinese Chinese Academy of Sciences the Prize Scholarship”(中国科学院院长优秀奖).
2022.11: 🎉🎉 Three full research papers are accepted at International Conference on Software Engineering (ICSE’23).
2022.05: 🎉🎉 I received the ACM Student Research Competition (SRC) at ICSE 2022, 1st Place, Graduate Category.
2020.09: 🎉🎉 I received the ACM Student Research Competition (SRC) at ASE 2020, 1st Place, Graduate Category.

📝 Publications

[TSE 2024] Software Testing with Large Language Models: Survey, Landscape, and Vision
IEEE Transactions on Software Engineering (CCF-A)
Junjie Wang, Yuchao Huang, Chunyang Chen, Zhe Liu, Song Wang, Qing Wang
[CHI 2024] 🏆 Unblind Text Inputs: Predicting Hint-text of Text Input in Mobile Apps via LLM
2024 CHI Conference on Human Factors in Computing Systems (CCF-A)
Zhe Liu, Chunyang Chen, Junjie Wang, Mengzhuo Chen, Boyu Wu, Yuekai Huang, Jun Hu, Qing Wang
[ICSE 2024] Make LLM a Testing Expert: Bringing Human-like Interaction to Mobile GUI Testing via Functionality-aware Decisions IEEE/ACM 46th International Conference on Software Engineering (CCF-A)
Zhe Liu, Chunyang Chen, Junjie Wang, Mengzhuo Chen, Boyu Wu, Xing Che, Dandan Wang, Qing Wang
[ICSE 2024] Testing the Limits: Unusual Text Inputs Generation for Mobile App Crash Detection with Large Language Model
IEEE/ACM 46th International Conference on Software Engineering (CCF-A)
Zhe Liu, Chunyang Chen, Junjie Wang, Mengzhuo Chen, Boyu Wu, Zhilin Tian, Yuekai Huang, Jun Hu, Qing Wang
[ICSE 2024] CrashTranslator: Automatically Reproducing Mobile Application Crashes Directly from Stack Trace
IEEE/ACM 46th International Conference on Software Engineering (CCF-A)
Yuchao Huang, Junjie Wang, Zhe Liu, Yawen Wang, Song Wang, Chunyang Chen, Yuanzhe Hu, Qing Wang
[ICSE 2023] Fill in the blank: Context-aware automated text input generation for mobile gui testing
IEEE/ACM 45th International Conference on Software Engineering (CCF-A)
Zhe Liu, Chunyang Chen, Junjie Wang, Xing Che, Yuekai Huang, Jun Hu, Qing Wang
[ICSE 2023] Ex pede Herculem: Augmenting Activity Transition Graph for Apps via Graph Convolution Network
IEEE/ACM 45th International Conference on Software Engineering (CCF-A)
Zhe Liu, Chunyang Chen, Junjie Wang, Yuhui Su, Yuekai Huang, Jun Hu, Qing Wang
[ICSE 2023] Context-aware Bug Reproduction for Mobile Apps
IEEE/ACM 45th International Conference on Software Engineering (CCF-A)
Yuchao Huang, Junjie Wang, Zhe Liu, Song Wang, Chunyang Chen, Mingyang Li, Qing Wang
[ICSE-Demo 2022] NaviDroid: A tool for Guiding Manual Android Testing via Hint Moves
IEEE/ACM 44th International Conference on Software Engineering - Demo (CCF-A)
Zhe Liu, Chunyang Chen, Junjie Wang, Yuhui Su, Qing Wang
[ASE 2022] The Metamorphosis: Automatic Detection of Scaling Issues for Mobile Apps
IEEE/ACM 37th International Conference on Automated Software Engineering (CCF-A)
Yuhui Su, Chunyang Chen, Junjie Wang, Zhe Liu, Dandan Wang, Shoubin Li, Qing Wang
[CHI 2022] Guided Bug Crush: Assist Manual GUI Testing of Android Apps via Hint Moves
2022 CHI Conference on Human Factors in Computing Systems (CCF-A)
Zhe Liu, Chunyang Chen, Junjie Wang, Yuekai Huang, Jun Hu, Qing Wang
[TSE 2022] Nighthawk: Fully Automated Localizing UI Display Issues via Visual Understanding
IEEE Transactions on Software Engineering (CCF-A)
Zhe Liu, Chunyang Chen, Junjie Wang, Yuekai Huang, Jun Hu, Qing Wang
[FSE-Demo 2020] OwlEyes-online: A Fully Automated Platform for Detecting and Localizing UI Display Issues
29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (CCF-A)
Yuhui Su*, Zhe Liu*, Chunyang Chen, Junjie Wang, Yuekai Huang, Jun Hu, Qing Wang
[ASE 2020] Owl Eyes: Spotting UI Display Issues via Visual Understanding
IEEE/ACM 35th International Conference on Automated Software Engineering (CCF-A)
Zhe Liu, Chunyang Chen, Junjie Wang, Yuekai Huang, Jun Hu, Qing Wang
[软件学报 2020] 移动应用程序中用户界面显示缺陷检测的经验研究
Journal of Software (软件学报)
Zhe Liu, Chunyang Chen, Junjie Wang, Xing Che, Yuhui Su, Qing Wang
[ESEM 2021] Characterizing and Predicting Good First Issues
ACM/IEEE 15th International Symposium on Empirical Software Engineering and Measurement (CCF-B)
Yuekai Huang, Junjie Wang, Song Wang, Zhe Liu, Dandan Wang, Qing Wang
[ESEM 2020] Quest for The Golden Approach: An Experimental Evaluation of Duplicate Crowdtesting Reports Detection
ACM/IEEE 14th International Symposium on Empirical Software Engineering and Measurement (CCF-B)
Yuekai Huang, Junjie Wang, Song Wang, Zhe Liu, Yuanzhe Hu, Qing Wang

ICSE 2024

Mobile applications have become a ubiquitous part of our daily life, providing users with access to various services and utilities. Text input, as an important interaction channel between users and applications, plays an important role in core functionality such as search queries, authentication, messaging, etc. However, certain special text (e.g., -18 for Font Size) can cause the app to crash, and generating diversified unusual inputs for fully testing the app is highly demanded. Nevertheless, this is also challenging due to the combination of explosion dilemma, high context sensitivity, and complex constraint relations. This paper proposes InputBlaster which leverages the LLM to automatically generate unusual text inputs for mobile app crash detection. It formulates the unusual inputs generation problem as a task of producing a set of test generators, each of which can yield a batch of unusual text inputs under the same mutation rule.

ICSE 2024

Automated Graphical User Interface (GUI) testing plays a crucial role in ensuring app quality, especially as mobile applications have become an integral part of our daily lives. Despite the growing popularity of learning-based techniques in automated GUI testing due to their ability to generate human-like interactions, they still suffer from several limitations, such as low testing coverage, inadequate generalization capabilities, and heavy reliance on training data. Inspired by the success of Large Language Models (LLMs) like ChatGPT in natural language understanding and question answering, we formulate the mobile GUI testing problem as a Q&A task. We propose GPTDroid, asking LLM to chat with the mobile apps by passing the GUI page information to LLM to elicit testing scripts, and executing them to keep passing the app feedback to LLM, iterating the whole process.

🎖 Honors and Awards

2023: 🏆 The ACM Student Research Competition (SRC) 2023 Grand Finals Winners, 1st Place, Graduate Category.
2023: 🎖 中国科学院院长优秀奖
2023: 🎖 北京市优秀毕业生
2023: 🎖 北京市三好学生
2023: 🎖 中国科学院大学优秀毕业生
2023: 🎖 中国科学院大学优秀学生干部
2023: 🎖 中国科学院大学优秀共青团员
2022: 🏆 The ACM Student Research Competition (SRC) at ICSE 2022, 1st Place, Graduate Category.
2022: 🎖 中国科学院大学三好学生标兵
2022: 🎖 中国科学院大学优秀学生干部
2022: 🎖 中国科学院软件研究所学术年会优秀海报奖
2021: 🎖 博士研究生国家奖学金
2021: 🎖 中国科学院大学三好学生标兵
2021: 🎖 中国科学院大学优秀学生干部
2021: 🎖 中国科学院软件研究所学术年会优秀海报奖
2020: 🏆 The ACM Student Research Competition (SRC) at ASE 2020, 1st Place, Graduate Category.
2020: 🎖 硕士研究生国家奖学金
2020: 🎖 中国科学院大学三好学生