Seongmin Lee

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 14

Top Topics

Convolutional Neural Networks

Low False Positive Rate

Program Slicing

Top Venues

ICSE (Companion Volume)

J. Syst. Softw.

Publications

Danushka Liyanage, Seongmin Lee, Chakkrit Tantithamthavorn, Marcel Böhme
Extrapolating Coverage Rate in Greybox Fuzzing. ICSE (2024)
Seongmin Lee, Dave W. Binkley, Robert Feldt, Nicolas Gold, Shin Yoo
Causal Program Dependence Analysis. CoRR (2021)
Seongmin Lee, Dave W. Binkley, Robert Feldt, Nicolas Gold, Shin Yoo
Observation-based approximate dependency modeling and its use for program slicing. J. Syst. Softw. 179 (2021)
Saeyoon Oh, Seongmin Lee, Shin Yoo
Effectively Sampling Higher Order Mutants Using Causal Effect. ICST Workshops (2021)
Saeyoon Oh, Seongmin Lee, Shin Yoo
Effectively Sampling Higher Order Mutants Using Causal Effect. CoRR (2021)
Seongmin Lee
Scalable and approximate program dependence analysis. ICSE (Companion Volume) (2020)
William B. Langdon, Westley Weimer, Justyna Petke, Erik M. Fredericks, Seongmin Lee, Emily Winter, Michail Basios, Myra B. Cohen, Aymeric Blot, Markus Wagner, Bobby R. Bruce, Shin Yoo, Simos Gerasimou, Oliver Krauss, Yu Huang, Michael C. Gerten
Genetic Improvement @ ICSE 2020. ACM SIGSOFT Softw. Eng. Notes 45 (4) (2020)
Seongmin Lee, Dave W. Binkley, Nicolas Gold, Syed S. Islam, Jens Krinke, Shin Yoo
Evaluating lexical approximation of program dependence. J. Syst. Softw. 160 (2020)
William B. Langdon, Westley Weimer, Justyna Petke, Erik M. Fredericks, Seongmin Lee, Emily Winter, Michail Basios, Myra B. Cohen, Aymeric Blot, Markus Wagner, Bobby R. Bruce, Shin Yoo, Simos Gerasimou, Oliver Krauss, Yu Huang, Michael C. Gerten
Genetic Improvement @ ICSE 2020. CoRR (2020)
Seongmin Lee, Shin Hong, Jungbae Yi, Taeksu Kim, Chul-Joo Kim, Shin Yoo
Classifying False Positive Static Checker Alarms in Continuous Integration Using Convolutional Neural Networks. ICST (2019)
Seongmin Lee, David W. Binkley, Robert Feldt, Nicolas Gold, Shin Yoo
MOAD: Modeling Observation-Based Approximate Dependency. SCAM (2019)
Seongmin Lee, David W. Binkley, Nicolas Gold, Syed S. Islam, Jens Krinke, Shin Yoo
MOBS: multi-operator observation-based slicing using lexical approximation of program dependence. ICSE (Companion Volume) (2018)
Seongmin Lee, Shin Yoo
Hyperheuristic Observation Based Slicing of Guava. SSBSE (2017)
Jeongju Sohn, Seongmin Lee, Shin Yoo
Amortised Deep Parameter Optimisation of GPGPU Work Group Size for OpenCV. SSBSE (2016)