Donghwan Shin

Lecturer (Assistant Professor)

University of Sheffield

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I am a lecturer (assistant professor in the American system) at the Department of Computer Science, University of Sheffield, Sheffield, UK.

My research and teaching interests lie in mutation testing, testing for ML-enabled cyber-physical systems (e.g., ML-enabled automated driving systems), and log analysis (e.g., model inference and anomaly detection). I have published many research papers at venues such as ICSE, ICST, ISSTA, and MODELS and journals such as TSE, EMSE, and STVR. Please see my Google Scholar page for details.

I did my PhD under the supervision of Prof. Doo-Hwan Bae at Korea Advanced Institute of Science and Technology (KAIST), South Korea. I hold a B.C. and M.S. in Computer Science, both from KAIST. This was followed by four years as a research associate/scientist at the SVV (Software Verification and Validation) group, led by Prof. Lionel Briand, at the Interdisciplinary Centre for ICT Security, Reliability, and Trust (SnT) of the University of Luxembourg. My full CV is available here

Research Interests

Featured Publications

Recent News

17 May 2024

Our paper titled "Systematic Evaluation of Deep Learning Models for Log-based Failure Prediction" has been accepted for publication in Empirical Software Engineering. 

14 April 2024

I received an ICSE 2024 Distinguished Reviewer award 🏆. ICSE is one of the top international conferences in software engineering. It's my first time receiving a reviewer award, so I'm quite excited. 

21 January 2024

Three new papers accepted! Mutation-based Consistency Testing for Evaluating the Code Understanding Capability of LLMs (CAIN 2024), Tuning the feedback controller gains is a simple way to improve autonomous driving performance (Control 2024), and Toward Automated Compliance Checking of Fund Activities Using  Runtime Verification Techniques (FinanSE 2024, extended abstract). See Publications for more details. 

14 December 2023

Our journal-first paper titled "Rigorous Assessment of Model Inference Accuracy using Language Cardinality" has been accepted at TOSEM. This is collaborative work with the University of Luxembourg and Imperial College London. 

7 November 2023

Happy to join as a PC member of SESoS 2024 and TestADS 2024. Please consider submitting your papers!

14 October 2023

Our journal-first paper titled "Identifying the Hazard Boundary of ML-enabled Autonomous Systems Using Cooperative Co-Evolutionary Search" has been accepted at TSE. This is collaborative work with the University of Luxembourg and the University of Ottawa.

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