YoungJae Kim
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
YoungJae Kim has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Jooyong Yi
UNIST, Ulsan, Republic of Korea
2 shared publications - Seungheon Han
UNIST, Ulsan, Republic of Korea
2 shared publications - Yechan Park
Department of Computer Science and Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
1 shared publication - Yeseung Lee
UNIST, Ulsan, Republic of Korea
1 shared publication
Latest Publications
- Open Access
- 12 April 2026
- Published by Association for Computing Machinery (ACM)
- p. 3761-3773
SymRadar: PoC-Centered Bounded Verification for Vulnerability Repair
- 12 April 2026
- Published by Association for Computing Machinery (ACM)
- p. 3761-3773
Open AccessSymRadar: PoC-Centered Bounded Verification for Vulnerability Repair
- Open Access
- 27 October 2024
- Published by Association for Computing Machinery (ACM)
- p. 1719-1731
Enhancing the Efficiency of Automated Program Repair via Greybox Analysis
In this paper, we pay attention to the efficiency of automated program repair (APR). Recently, an efficient patch scheduling algorithm, Casino, has been proposed to improve APR efficiency. Inspired by fuzzing, Casino adaptively chooses the next patch candidate to evaluate based on the results of previous evaluations. However, we observe that Casino utilizes only the test results, treating the patched program as a black box. Inspired by greybox fuzzing, we propose a novel patch-scheduling algorithm, Gresino, which leverages the internal state of the program to further enhance APR efficiency. Specifically, Gresino monitors the hit counts of branches observed during the execution of the program and uses them to guide the search for a valid patch. Our experimental evaluation on the Defects4J benchmark and eight APR tools demonstrates the efficacy of our approach.
- 27 October 2024
- Published by Association for Computing Machinery (ACM)
- p. 1719-1731
Open AccessEnhancing the Efficiency of Automated Program Repair via Greybox Analysis
In this paper, we pay attention to the efficiency of automated program repair (APR). Recently, an efficient patch scheduling algorithm, Casino, has been proposed to improve APR efficiency. Inspired by fuzzing, Casino adaptively chooses the next patch candidate to evaluate based on the results of previous evaluations. However, we observe that Casino utilizes only the test results, treating the patched program as a black box. Inspired by greybox fuzzing, we propose a novel patch-scheduling algorithm, Gresino, which leverages the internal state of the program to further enhance APR efficiency. Specifically, Gresino monitors the hit counts of branches observed during the execution of the program and uses them to guide the search for a valid patch. Our experimental evaluation on the Defects4J benchmark and eight APR tools demonstrates the efficacy of our approach.