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ICSE 2023
Sun 14 - Sat 20 May 2023 Melbourne, Australia
Shin Yoo

Registered user since Fri 9 Jun 2017

Name:Shin Yoo

Shin Yoo is a tenured Associate Professor in the School of Computing, Korea Advanced Institute of Science and Technology (KAIST) and leads the Computational Intelligence for Software Engineering (COINSE) group (https://coinse.kaist.ac.kr). He received his PhD from King’s College London in 2009. His research interests include search based software engineering, software testing, fault localisation, and genetic improvements. He received the ACM SIGEVO HUMIES Silver Medal in 2017 for the human competitive application of genetic programming to fault localisation research. He is currently an associate editor for Journal of Empirical Software Engineering and ACM Transactions on Software Engineering and Methodology. He regularly serves in program committees of international conferences in the area of software engineering and software testing. Additionally, he served as the Program Co-chair of International Symposium on Search Based Software Engineering (SSBSE) in 2014, the Program Co-chair of IEEE International Conference on Software Testing, Verification and Validation (ICST) in 2018, the Program Co-chair of ICSE New Ideas and Emerging Results (NIER) track in 2020, and the general chair of SSBSE 2022.

Country:South Korea
Research interests:Search Based Software Engineering


DeepTest 2023 Committee Member in Program Committee within the DeepTest 2023-track
GI 2023 Towards Objective-Tailored Genetic Improvement Through Large Language Models
ICSE 2023 Predictive Mutation Analysis via Natural Language Channel in Source Code
Fonte: Finding Bug Inducing Commits from Failures
Arachne: Search Based Repair of Deep Neural Networks
Artifact for Fonte: Finding Bug Inducing Commits From Failures
Large Language Models are Few-shot Testers: Exploring LLM-based General Bug Reproduction
GLAD: Neural Predicate Synthesis to Repair Omission Faults
A Replication of Large Language Models are Few-shot Testers: Exploring LLM-based General Bug Reproduction
AST 2023 Lessons from 10 Years of Automated Debugging Research
Panel Discussions and AST Summary Remarks
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