UT Dallas Doctoral Student Miao Miao Wins First Place at ICSE 2025 ACM Student Research Competition

Miao Miao, a doctoral student in The University of Texas at Dallas Department of Computer Science working under the guidance of Professor Shiyi Wei, has earned international recognition for her innovative research in software testing. At the 2025 International Conference on Software Engineering (ICSE), the top academic venue in the field, Miao won first place in the prestigious ACM Student Research Competition (SRC) for her project, Program Feature-based Fuzzing Benchmarking.

Fuzzing or fuzz testing is a powerful and widely adopted software testing technique that automatically generates millions of random test inputs to detect bugs and security vulnerabilities. As Miao explained, “Fuzzing is an automated testing technique that has proven highly effective in detecting bugs in software … Crashes that allow malicious code execution, data leakage, or trigger denial-of-service (DoS) are considered vulnerabilities.”

Despite its popularity, the evaluation of fuzzing tools has long lacked depth. “There is limited understanding of how and why greybox fuzzers work, particularly concerning the impact of program features on their performance,” Miao explained. This knowledge gap means researchers and developers may choose suboptimal tools, potentially missing critical security flaws.Miao’s research addresses this gap head-on. By analyzing 25 fuzzing studies, she identified seven key program features, such as control-flow complexity and data structure handling, that significantly influence fuzzer performance. Using these features, Miao built a benchmark suite of 153 customizable test programs to more intelligently evaluate fuzzers. Her study revealed that the same fuzzer could perform very differently, depending upon the characteristics of the program being tested.

Miao’s research addresses this gap head-on. By analyzing 25 fuzzing studies, she identified seven key program features, such as control-flow complexity and data structure handling, that significantly influence fuzzer performance. Using these features, Miao built a benchmark suite of 153 customizable test programs to more intelligently evaluate fuzzers. Her study revealed that the same fuzzer could perform very differently, depending upon the characteristics of the program being tested.

“Although several important fuzzing benchmarks exist, they all only focus on bugs in programs and do not explain performance differences across fuzzers,” Miao said. “Our benchmark aims to complement these existing tools by evaluating fuzzers on a set of programs with varying features and analyzing how these features influence fuzzing performance.”

Miao’s research not only introduces a new dimension of insight for software engineers but also offers a practical tool for developers in industry and academia. “This work is significant because fuzz testing is very important in system security testing,” she explained. “Our benchmark improves the explainability of fuzzer behaviors, so we not only know which fuzzer performs better but also understand the reasons behind performance differences. This helps in developing or selecting the most effective fuzzer for specific use cases.”

Wei praised the depth and rigor of her work: “Miao’s research is not only technically rigorous but also provides the community with a much-needed tool to better understand and improve fuzz testing practices. I’m incredibly proud of her achievement.”

Her award-winning project has also been selected for presentation in the research track at the 2025 International Symposium on Software Testing and Analysis (ISSTA), another top venue in software engineering. At ICSE, she also presented a second paper from Wei’s lab, further showcasing her broad contributions to the field.

Miao’s path to research excellence is fueled by deep curiosity and a passion for building secure and reliable software systems. “I was drawn to software engineering research because of its direct impact on how we build and secure software systems,” she said. “When I started exploring fuzzing, I realized how powerful it was, yet there was so much room to improve how we evaluate and understand it.”

She’s especially inspired by the growing importance of fuzzing in emerging technologies, such as autonomous vehicles, virtual and augmented reality and machine learning systems. “We will likely see the development of many domain-specific fuzzers,” she noted. “Additionally, universally accepted benchmarks tailored to specific domains will become more prevalent. These consistent frameworks will help drive the development of more robust fuzzers.”

Looking ahead, Miao is working on several new research projects. One focuses on analyzing fuzzing blockers, barriers within fuzzers or programs that hinder effective testing. “This work aims to provide deeper insights into how fuzzer design choices and program features influence bug discovery and code coverage,” she said. She is also co-developing a visualization framework for comparing fuzzing metrics that moves beyond traditional measurements like code coverage. “We propose a taxonomy of visualization analysis tasks, which is a foundational step toward user-centered visualization tools,” she added.

Beyond her research, Miao is also a dedicated educator and leader. She was named the Jonsson School of Engineering and Computer Science’s Best Teaching Assistant in 2024 and received the Mary and Richard Templeton Graduate Fellowship for her academic excellence and service contributions.

Reflecting on her time at UT Dallas, Miao credited her advisor and the department for their guidance and support. “Dr. Shiyi Wei has been an incredible mentor throughout my research journey,” she said. “He provided technical guidance and encouraged me to explore ambitious ideas. The Computer Science Department created a supportive environment with access to research resources and a vibrant community of peers and faculty.”

To other students interested in program analysis or software reliability research, Miao offered heartfelt advice: “Stay curious and don’t be afraid to dive deep into challenging problems. These fields require strong theoretical and practical skills, so a solid understanding of programming languages and compilers is key. Read widely, experiment with your ideas — even the ambitious ones — and seek out mentors and peers to learn from. Collaboration and feedback are essential.”

As for her long-term plans, Miao hopes to pursue a career as a professor in computer science and software engineering. “I’m passionate about both research and teaching, and I hope to share the knowledge and opportunities I’ve gained at UT Dallas with future students, supporting and inspiring them as they embark on their own journeys.”

Miao Miao’s story is one of determination, intellectual curiosity and vision. Through her research, she is advancing the field of software engineering and contributing to the development of a more secure and reliable digital future.