UC engineering student merges human language, computer science

Zedong Peng is a doctoral candidate in computer science and engineering at UC

By Lindsey Osterfeld Email Lindsey

7 minute read August 7, 2023

Zedong Peng came to the University of Cincinnati to continue his research in software engineering, focusing on natural language processing and metamorphic testing. At UC he has served as a teaching assistant for several courses in the Department of Electrical and Computer Engineering, has published several peer-reviewed papers and was recently named Graduate Student Engineer of the Month by UC's College of Engineering and Applied Science.

How did you end up choosing UC? What drew you here?

After completing my bachelor's and Master of Business Administration degrees at universities in the U.S., I wanted to pursue my interest in software engineering by obtaining a Master of Science degree. My passion for this field remained strong, and I felt that pursuing a Ph.D. would broaden my research horizons and help me become a professional researcher. During my research, I came across papers from Dr. Nan Niu's lab, which piqued my interest. I had the opportunity to talk to him and was impressed with his knowledge and expertise. His encouragement led me to apply for the Ph.D. program in computer science at UC.

Why did you choose your field of study?

I chose my field of study in software engineering and natural language processing because of my passion for exploring the intersection of computer science and human language. During my doctoral studies at the University of Cincinnati, I focused on metamorphic testing in scientific software and natural language processing in requirements engineering. Through my research, I discovered the potential for using natural language processing to improve the quality of software testing, which fueled my interest in this field.

Briefly describe your research work? Why does it interest you?

Zedong Peng.

My early work focused on developing an automated approach for identifying abstractions for supporting requirements-based testing. Here, an abstraction is a term that is particularly significant in a given domain. This approach utilizes relevant Wikipedia pages as a domain corpus that is independent from any specific software system and defines five novel patterns based on part-of-speech tagging (categorizing words into nouns, verbs, etc.) and dependency parsing (determining the grammatical structure of a sentence). The abstractions are framed in the form of key-value pairs for better testability, where the "key" helps locate what to test, and the "value" helps guide how to test it by feeding in concrete data. The results of evaluating this approach with six software systems in two application domains (electronic health records and web conferencing) have shown that the abstractions generated by this approach are more accurate than those generated by a state-of-the-art technique. This work received the Best Research Paper Award at the 29th Institute of Electrical and Electronics Engineers International Requirements Engineering Conference.

Furthermore, I have proposed a fully automatic approach for classifying input and output variables from scientific software's user manual, mining metamorphic relations, and generating test inputs. This approach utilizes a machine learning algorithm to classify input and output variables and generate metamorphic test inputs. This approach can be applied to scientific software operating in a large multi-parameter input space, which is challenging to test manually.

I am also interested in understanding the scientific software quality assurance workflow and how metamorphic testing fits into it. I have conducted an artifact analysis followed by stakeholder interviews and literature analysis, which received Best Emerging Results and Vision Paper Award at the 15th ACM/IEEE international symposium on empirical software engineering and measurement.

What are some of the most impactful experiences during your time at UC?

I received the Robert J. Herbold Fellowship in 2021, funded by Robert J. Herbold, the president of the Herbold Foundation, managing director of the Herbold Group, LLC, and the retired chief operating officer of Microsoft Corporation. I was honored to interact with him and ask him questions.

I was also able to improve my leadership skills through the Research Experiences for Teachers program in the summer of 2021. In this program, a high school in-service teacher joined our research group and I served as a Graduate Research Assistant to support my adviser Dr. Nan Niu to mentor the teacher. We conducted a norm classification tool in the Google Collab platform to enrich his content delivery in his classrooms. I was responsible for collecting the reading materials for the teacher, providing the technical support for method implementation and guiding our RET teacher's programming skills in Python on the Google Collab platform. Later, we successfully published a paper titled "Towards Norm Classification: An Initial Analysis of HIPAA Breaches" at the 29th IEEE Engineers International Requirements Engineering Conference Workshops.

What are a few accomplishments you are most proud of?

I have published 13 peer-reviewed papers during my Ph.D. study at the University of Cincinnati, including three journal articles, ten conference and workshop papers, and two best paper awards.

I have been invited to serve on the program committee for the IEEE International Conference on Information Reuse and Integration for Data Science and the ACM International Conference for Information and Management.

I served as a student volunteer at three international conferences in 2020 and 2021 where I spent extra effort in preparing meeting sessions, coordinating with session chairs and presenters, and assisting in the virtual banquet. I became familiar with various meeting platforms, like Webex, Zoom, Midspace (formerly Clowdr), et cetera. I am honored to have received the Outstanding Service Award at IRI 2020.

When do you expect to graduate? What are your plans after earning your degree?

I anticipate graduating in 2023. After earning my degree, I will be starting a new position this fall as an assistant professor in the department of computer science at the University of Montana. I am passionate about contributing to the advancement of knowledge in my field and believe that working in a university setting will provide me with the ideal platform to achieve my goals. I look forward to the opportunity to engage with students and colleagues, conduct research, publish papers and contribut to the academic community.

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Featured Image at top: Photo/Pixabay.