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Postdoctoral Researcher Software Analysis Laboratory Dept. of Computer Science and Engineering, Korea University Email: minseok_jeon@korea.ac.kr [CV] |
Education
- 2017.03 ~ 2023.02, Integrated M.S. & Ph.D. in Computer Science and Engineering. Korea University
- Advisor: Hakjoo Oh
- 2011.03 ~ 2017.02, B.S. Dept. of Computer Science, Korea University
Research Interests
- Program Analysis: program analysis for automatically detecting software bugs and vulnerabilities.
- Machine Learning: programming language-based machine learning for accurate, interpretable, and explainable AI.
Publications
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Automating Endurance Test for Flash-based Storage Devices in Samsung Electronics
Jinkook Kim, Minseok Jeon, Sejeong Jang, and Hakjoo Oh
ICST 2023 : International Conference on Software Testing, Verification and Validation (Industry Track)
[pdf] -
Return of CFA: Call-Site Sensitivity Can Be Superior to Object Sensitivity Even for Object-Oriented Programs
Minseok Jeon and Hakjoo Oh
POPL 2022 : ACM SIGPLAN Symposium on Principles of Programming Languages
[pdf] [teaser video] [slides] [artifact] -
A Practical Algorithm for Learning Disjunctive Abstraction Heuristics in Static Program Analysis
Donghoon Jeon, Minseok Jeon, and Hakjoo Oh
Information and Software Technology, Volume 135, July 2021
[link] -
Learning Graph-based Heuristics for Pointer Analysis without Handcrafting Application-Specific Features
Minseok Jeon, Myungho Lee, and Hakjoo Oh
OOPSLA 2020: ACM Conference on Object-Oriented Programming, Systems, Languages, and Applications
[pdf] [slides] [artifact] -
A Machine-Learning Algorithm with Disjunctive Model for Data-Driven Program Analysis
Minseok Jeon*, Sehun Jeong*, Sungdeok Cha, and Hakjoo Oh (*co-first author)
TOPLAS 2019: ACM Transactions on Programming Languages and Systems
[pdf] -
Precise and Scalable Points-to Analysis via Data-Driven Context Tunneling
Minseok Jeon, Sehun Jeong, and Hakjoo Oh
OOPSLA 2018: ACM Conference on Object-Oriented Programming, Systems, Languages, and Applications
[pdf] [link] [poster] [slides] -
Data-Driven Context-Sensitivity for Points-to Analysis
Sehun Jeong*, Minseok Jeon*, Sungdeok Cha, and Hakjoo Oh (*co-first author)
OOPSLA 2017: ACM Conference on Object-Oriented Programming, Systems, Languages, and Applications
[pdf] [link] [poster] [slides]
Talks
- Return of CFA: Call-Site Sensitivity Can Be Superior to Object Sensitivity Even for Object-Oriented Programs. Paper presentation at POPL 2022. STAAR Workshop. Jeju. Feb 11 2022 [slides]
- Return of CFA: Call-Site Sensitivity Can Be Superior to Object Sensitivity Even for Object-Oriented Programs. Paper presentation at POPL 2022. Philadelphia, USA. Jan 19 2022 [slides]
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Learning Graph-based Heuristics for Pointer Analysis without Handcrafting Application-Specific Features. KSC 2020.
[video(korean)]
- Learning Graph-based Heuristics for Pointer Analysis without Handcrafting Application-Specific Features. Paper presentation at OOPLSA 2020, Online Nov. 20 2020. [slides] [video]
- Precise and Scalable Points-to Analysis via Data-Driven Context Tunneling. Paper presentation at OOPSLA2018. BOSTON, USA. NOV 8 2018 [slides]
- Data-Driven Context-Sensitivity for Points-to Analysis. KCC2018. June 2018
- Data-Driven Context-Sensitivity for Points-to Analysis. KCSE2018. Jan 2018 [slides]
Project
- Bachelor Degree Project : Enough to check Collatz Conjecture for 16k+11 [pdf]
Trips
- POPL 2022, Philadelphia, USA. 2022/Jan/17 - 2022/Jan/23. [report(Korean)]
- OOPSLA 2019, Athens, Greece. 2019/Oct/20 - 2019/Oct/26. [report(Korean)]
- OOPSLA 2018, Boston, USA. 2018/Nov/4 - 2018/Nov/11. [report(Korean)]
- OOPSLA 2017, Vancouver, Canada. 2017/Oct/23 - 2017/Oct/27. [report(Korean)]