Publications
Orbis: Guiding Symbolic Execution Techniques to Maximize Option-Related Branch Coverage
Minjong Kim, Sungjae Hwang, and Sooyoung Cha
ASE 2026: IEEE/ACM International Conference on Automated Software Engineering (accepted)
[pdf]
TuneScape: Visualizing Multi-Tuner Parameter Optimization Logs
Donghee Hong, Minjong Kim, Sooyoung Cha, and Jaemin Jo
IEEE VIS 2026: IEEE Visualization and Visual Analytics Conference (Short Paper) (conditionally accepted)
[pdf]
Reducing Coverage-Equivalent Inputs in Grammar-based Fuzzing by Avoiding Recurrent Rule Sequences
Jaehan Yoon, Yunji Seo, Hakjoo Oh, and Sooyoung Cha
FSE 2026: ACM International Conference on the Foundations of Software Engineering
Symetra: Visual Analytics for the Parameter Tuning Process of Symbolic Execution Engines
Donghee Hong, Minjong Kim, Sooyoung Cha, and Jaemin Jo
EuroVis 2026: Eurographics Conference on Visualization
Enhancing Symbolic Execution with Self-Configuring Parameters
Minjong Kim and Sooyoung Cha
ICSE 2026: International Conference on Software Engineering
TopSeed: Learning Seed Selection Strategies for Symbolic Execution from Scratch
Jaehyeok Lee and Sooyoung Cha
ICSE 2025: International Conference on Software Engineering
FeatMaker: Automated Feature Engineering for Search Strategy of Symbolic Execution
Jaehan Yoon and Sooyoung Cha
FSE 2024: ACM International Conference on the Foundations of Software Engineering
Learning Seed-Adaptive Mutation Strategies for Greybox Fuzzing
Myungho Lee, Sooyoung Cha, and Hakjoo Oh
ICSE 2023: International Conference on Software Engineering
Enhancing Dynamic Symbolic Execution by Automatically Learning Search Heuristics
Sooyoung Cha, Seongjoon Hong, Jiseong Bak, Jingyoung Kim, Junhee Lee, and Hakjoo Oh
TSE: IEEE Transactions on Software Engineering, Volume 48, No. 9, 2022, Pages 3640- 3663.
[pdf] [tool]
SymTuner: Maximizing the Power of Symbolic Execution by Adaptively Tuning External Parameters
Sooyoung Cha, Myungho Lee, Seokhyun Lee, and Hakjoo Oh
ICSE 2022: International Conference on Software Engineering
🏅ACM SIGSOFT Distinguished Paper Award
Making Symbolic Execution Promising by Learning Aggressive State-Pruning Strategy
Sooyoung Cha and Hakjoo Oh
ESEC/FSE 2020: ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering.
[pdf] [tool] [slides] [teaser video] [video]
Effective White-Box Testing of Deep Neural Networks with Adaptive Neuron-Selection Strategy
Seokhyun Lee, Sooyoung Cha, Dain Lee and Hakjoo Oh
ISSTA 2020: The ACM SIGSOFT International Symposium on Software Testing and Analysis.
🏅ACM SIGSOFT Distinguished Paper Award
[pdf] [tool]
Concolic Testing with Adaptively Changing Search Heuristics
Sooyoung Cha and Hakjoo Oh
ESEC/FSE 2019: ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering.
[pdf] [tool] [slides]
A Scalable Learning Algorithm for Data-Driven Program Analysis
Sooyoung Cha, Sehun Jeong, and Hakjoo Oh
Information and Software Technology, Volume 104, 2018, Pages 1-13, ISSN 0950-5849.
[pdf] [link]
Template-Guided Concolic Testing via Online Learning
Sooyoung Cha, Seonho Lee, and Hakjoo Oh
ASE 2018: IEEE/ACM International Conference on Automated Software Engineering.
[pdf] [tool] [slides]
Automatically Generating Search Heuristics for Concolic Testing
Sooyoung Cha, Seongjoon Hong, Junhee Lee, and Hakjoo Oh
ICSE 2018: International Conference on Software Engineering.
[pdf] [tool] [slides]
Learning a Strategy for Choosing Widening Thresholds from a Large Codebase
Sooyoung Cha, Sehun Jeong, and Hakjoo Oh
APLAS 2016: Asian Symposium on Programming Languages and Systems.
[pdf] [slides]