Korea University · Environmental Science
Jinho Jung 교수의 연구실은 소프트웨어 시스템의 성능과 안정성 향상을 위한 자동화된 버그 탐지 기술, 특히 퍼지드(fuzzing) 기반의 테스팅 기법을 핵심으로 삼고 있습니다. 특히 윈도우 운영체제 환경에서의 성능 회귀 버그 탐지 및 DBMS의 최적화 문제 해결에 초점을 맞추고 있으며, 이와 더불어 환경 공학 분야에서도 수문학적 변수와 기후 변화 영향을 고려한 생물 분포 모델링 및 오존 미세거품 기반 오염물질 제거 기술에 대한 연구도 진행하고 있습니다. 이러한 다학제적 접근을 통해 소프트웨어와 환경 기술의 융합적 해결책을 모색하고 있습니다.
Figures are computed from collected data and may differ slightly.
The practical art of constructing database management systems (DBMSs) involves a morass of trade-offs among query execution speed, query optimization speed, standards compliance, feature parity, modularity, portability, and other goals. It is no surprise that DBMSs, like all complex software systems, contain bugs that can adversely affect their performance. The performance of DBMSs is an important metric as it determines how quickly an application can take in new information and use it to make n
Fuzzing is an emerging technique to automatically validate programs and uncover bugs. It has been widely used to test many programs and has found thousands of security vulnerabilities. However, existing fuzzing efforts are mainly centered around Unix-like systems, as Windows imposes unique challenges for fuzzing: a closed-source ecosystem, the heavy use of graphical interfaces and the lack of fast process cloning machinery.
In this study, water flow rate and quality variables that restrict freshwater fish distribution were incorporated in species distribution modeling to evaluate the impacts of climate change. A maximum entropy model (MaxEnt) was used to predict the distribution of 76 fish species in the present (2012–2014) and in the future (2025–2035 and 2045–2055) based on representative concentration pathway (RCP) 4.5 and RCP 8.5 scenarios for five major river basins (Han, Nakdong, Geum, Seomjin, and Yeongsan)
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