Research

Our research focuses on advancing the fields of Software Engineering, Deep Learning, and Human-Computer Interaction. Led by Prof. Dr. Chen, we apply Machine Learning, HCI, and light-weight program analysis technologies to tackle challenges in the following key areas:

1. AI4SE: AI(LLM)-assisted Automated Software Development
   • Automated UI design and source code generation
   • Automated software testing including GUI testing, functional testing, and bug reproduction
   • Software usability and accessibility
   • AI-empowered software repositories mining
2. SE4AI: AI Deployment into Software
   • Development of AI software like voice assistants
   • Robustness, security, and privacy of AI 

For AI4SE, we expect to boost software developers' productivity while also ensuring the software quality. For SE4AI, our goal is to facilitate the deployment of AI, especially LLM into the practical software while ensuring its efficiency, reliability, and security. By studying real-world software which is the natural host of AI, our ultimate goal is to explore effective human-AI collaboration in the future.

Note that for both directions, recently, we have put most of efforts into the emerging Large Language Model, and finished a list of latest LLM relevant publications. We also developed a brand new course named "Foundation and Application of Generative AI" which will be delivered to our students every semester.

Located at the Technical University of Munich Campus Heilbronn, Germany, our team collaborates with industry partners and academic institutions worldwide to drive advancements in these critical areas of research. We are open to different kinds of collaboration and welcome contact.

Awards

• Best Paper Honorable Mention in CHI 2024 
• Discovery Early Career Researcher Award (DECRA) from Australian Research Council
• ACM SIGSOFT Early Career Researcher Award 2023
• ACM SIGSOFT Distinguished Paper Award in ICSE 2023 
• ACM SIGSOFT Distinguished Paper Award in ICSE 2021 
• Dean's Award for Research Impact (Economic and Social Impact) in Faculty of IT, Monash University.
• Facebook Research Award in Probability and Programming 2020
• ACM SIGSOFT Distinguished Paper Award in ICSE 2020 
• ACM SIGSOFT Distinguished Paper Award in ASE 2018 
• Best Paper Award in SANER 2016 
• Best Tool Demo in ASE 2016 

Selected Recent Publications

1. [TSE-24] Software Testing with Large Language Model: Survey, Landscape, and Vision

   IEEE Transactions on Software Engineering

   Junjie Wang, Yuchao Huang, Chunyang Chen, Zhe Liu, Song Wang, Qing Wang

2. [UIST-24] GPTVoiceTasker: LLM-Powered Virtual Assistant for Smartphone

   ACM Symposium on User Interface Software and Technology

   Minh Duc Vu, Han Wang, Zhuang Li, Jieshan Chen, Shengdong Zhao, Zhenchang Xing, Chunyang Chen

3. [CHI-24] MUD: Towards a Large-Scale and Noise-Filtered UI Dataset for Modern Style UI Modeling

   ACM CHI conference on Human Factors in Computing Systems

   Sidong Feng, Suyu Ma, Han Wang, David Kong, Chunyang Chen

4. [CHI-24] Unblind Text Inputs: Predicting Hint-text of Text Input in Mobile Apps via LLM

   ACM CHI conference on Human Factors in Computing Systems

   Zhe Liu, Chunyang Chen, Junjie Wang, Mengzhuo Chen, Boyu Wu, Yuekai Huang, Jun Hu, Qing Wang

5. [ICSE-24] Make LLM a Testing Expert: Bringing Human-like Interaction to Mobile GUI Testing via Functionality-aware Decisions

   The 46th International Conference on Software Engineering

   Zhe Liu, Chunyang Chen, Junjie Wang, Mengzhuo Chen, Boyu Wu, Xing Che, Dandan Wang, Qing Wang

6. [ICSE-24] Testing the Limits: Unusual Text Inputs Generation for Mobile App Crash Detection with Large Language Model

   The 46th International Conference on Software Engineering

   Zhe Liu, Chunyang Chen, Junjie Wang, Mengzhuo Chen, Boyu Wu, Zhilin Tian, Yuekai Huang, Jun Hu, Qing Wang

7. [ICSE-24] Prompting Is All Your Need: Automated Android Bug Replay with Large Language Models

   The 46th International Conference on Software Engineering

   Sidong Feng, Chunyang Chen