Dr Donghwan Shin

简介

Dr Donghwan Shin is a Senior Lecturer in Testing in the School of Computer Science, University of Sheffield since 2022. He did his BSc (2006-2010), MSc (2010-2012), and PhD (2012-2018) at KAIST, South Korea. This was followed by four years as a research associate (2018-2020) and research scientist (2020-2022) at SnT, University of Luxembourg. His work has been funded by the EPSRC (UK) and the National Research Foundation of Korea (South Korea).

代表成果

• Lévai Z, Shin D & McMinn P (2026) A comprehensive empirical and theoretical analysis of batching algorithms for efficient, safe, parallel mutation analysis in rust. ACM Transactions on Software Engineering and Methodology. View this article in WRRO
• Gu R, Rojas JM & Shin D (2025) Software testing for extended reality applications: a systematic mapping study. Automated Software Engineering, 32(2). View this article in WRRO
• Khan ZA, Shin D, Bianculli D & Briand LC (2024) Impact of log parsing on deep learning-based anomaly detection. Empirical Software Engineering, 29(6). View this article in WRRO
• Biagiola M, Cardozo N, Khomh F, Riccio V, Shin D & Stocco A (2024) The 5thWorkshop on Testing for Deep Learning and Deep Learning for Testing (DeepTest 2024). Proceedings 2024 IEEE ACM International Workshop on Deep Learning for Testing and Testing for Deep Learning Deeptest 2024, VII.
• Hadadi F, Dawes JH, Shin D, Bianculli D & Briand L (2024) Systematic evaluation of deep learning models for log-based failure prediction. Empirical Software Engineering, 29. View this article in WRRO
• Clun D, Shin D, Filieri A & Bianculli D (2024) Rigorous assessment of model inference accuracy using language cardinality. ACM Transactions on Software Engineering and Methodology, 33(4), 1-39. View this article in WRRO
• Shin Y-J, Shin D & Bae D-H (2024) Virtual environment model generation for CPS goal verification using imitation learning. ACM Transactions on Embedded Computing Systems, 23(1), 1-29. View this article in WRRO
• Baek Y-M, Cho E, Shin D & Bae D-H (2024) An extensible modeling method supporting ontology-based scenario specification and domain-specific extension. International Journal of Software Engineering and Knowledge Engineering, 34(1), 91-162. View this article in WRRO
• Sharifi S, Shin D, Briand LC & Aschbacher N (2023) Identifying the hazard boundary of ML-enabled autonomous systems using cooperative co-evolutionary search. IEEE Transactions on Software Engineering, 49(12), 5120-5138. View this article in WRRO
• Biagiola M, Cardozo N, Shin D, Khomh F, Stocco A & Riccio V (2023) Summary of the fourth international workshop on deep learning for testing and testing for deep learning (DeepTest 2023). ACM SIGSOFT Software Engineering Notes, 48(4), 39-40. View this article in WRRO