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세미나 (Seminar)대학원 세미나 (3월 18일, Queens University 신지호 박사) | The 2nd Graduate Seminar (Spring 2026)

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2026-1학기 전산전자공학대학원 두 번째 세미나 강의를 소개합니다. We are pleased to announce the commencement of the 2026 Spring Semester Seminar Series for the Graduate School of Computer Science and Electrical Engineering. This weekly forum serves as a cornerstone for academic exchange, bringing together students, faculty, and industry experts to explore the frontiers of modern technology.

  • 강사(Speaker): 신지호 박사 (Queens University)
  • 제목(Title): Rethinking AI for Unit Test Generation: Adaptation, Evaluation, and Retrieval
  • 일시(Date): 3월 18일 수요일, 오전 11시 30분 | March 18, Wednesday
  • 장소(Venue): 온라인 Online (ZOOM: https://handong.zoom.us/j/8067967335)
  • 발표언어(Language): 영어
  • 초록(Abstract):
  • Unit test generation has re-emerged as a promising application of AI for software engineering, driven by recent advances in large language models and code generation systems. However, progress in this area depends on more than generating plausible tests at scale. It also requires methods that adapt effectively to the testing domain, evaluation criteria that reflect true test adequacy, and generation strategies that remain robust across realistic development settings. In this seminar, I will present a research trajectory that examines these challenges through three stages of unit test generation research. First, I will discuss how domain adaptation can improve code model-based unit test case generation. Next, I will examine the evaluation problem through work on neural test oracle generation, showing why commonly used metrics may not adequately capture functional quality. Finally, I will look at recent advances in retrieval-augmented test generation and assess how far these approaches move us towards more reliable and practical test generation. Taken together, these studies show that the central challenge in AI-based unit test generation is not only generating more tests, but generating tests that are meaningful, trustworthy, and evaluated in ways that reflect real software engineering needs.


  • 문의 (Inquiry): 054-260-3150(BK21 AI사업단)


본 세미나는 온라인으로 진행됩니다. 학부생, 대학원생, 교직원 누구나 참여 가능하니 많은 관심과 참여 바랍니다. This seminar will be conducted online. We welcome all undergraduate students, graduate students, faculty, and staff to join us. We look forward to your interest and active participation.

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Phone. 054-260-1414, 1378    Fax. 054-260-1976
E-mail. csee@handong.edu
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