Sooyoung Cha (차수영)

News

• I am always looking for motivated graduate/undergraduate students and postdocs to work with. 

For more detailed information, see recruitment, publications, talks, or send me an email.  

Research Areas

My research aims to develop software analysis techniques for safe and reliable software. In particular, 

• Data-driven software testing for automatically detecting software bugs [youtube] 

• Machine learning guided static analysis

• Neural network testing

Educational Background

• 2016 ~ 2021, Ph.D. Computer Science and Engineering, Korea University

• 2014 ~ 2016, M.S. Computer Science and Engineering, Korea University

• 2008 ~ 2014, B.S. Computer Science and Engineering, Sejong University

Employed Positions

• 2021.09 ~ present,  Assistant Professor, Dept. of Computer Science and Engineering, Sungkyunkwan University

• 2021.03 ~ 2021.08, Research Professor, Korea University

Publications

• 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

[pdf] [tool] 

• Learning Seed-Adaptive Mutation Strategies for Greybox Fuzzing
  Myungho Lee, Sooyoung Cha, and Hakjoo Oh

ICSE 2023: International Conference on Software Engineering

[pdf] [tool] 

• 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

[pdf] [tool] [slides] [video]

• 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.
  [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]