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ORCIDDonghwan Shin 0001
Person information
- affiliation: University of Sheffield, School of Computer Science, UK
- affiliation: University of Luxembourg
- affiliation (PhD 2018): KAIST, Daejeon, Republic of Korea
Other persons with the same name
- Donghwan Shin — disambiguation page
- Donghwan Shin 0002 — Mark Any Inc., Seoul, Korea
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2020 – today
- 2026
[j17]Ruizhen Gu, José Miguel Rojas
, Donghwan Shin:
Automated testing of prevalent 3D user interactions in virtual reality applications. Autom. Softw. Eng. 33(3): 78 (2026)- [c34]Zalán Lévai, Donghwan Shin, Phil McMinn:
Dynamic Mutation Scheduling: Highly Parallel, Efficient Evaluation of Mutations for Rust Programs through Program Splitting. ICST 2026: 146-157 - [c33]Zalán Lévai, Donghwan Shin, Phil McMinn:
mutest-rs: Flexible, Efficient Mutation Analysis Tool for Rust Programs, using Extensive Static Analysis. ICST 2026: 216-220 - [c32]Olek Osikowicz, Phil McMinn, Wei Xing, Donghwan Shin:
Multi-Fidelity Bayesian Optimization for Simulation Based Autonomous Driving Systems Testing. IV 2026: 187-194 - [i26]Nathan Shaw, Sanjeetha Pennada, Robert M. Hierons, Donghwan Shin:
A Systematic Mapping Study on the Debugging of Autonomous Driving Systems. CoRR abs/2601.04293 (2026) - [i25]Beomsu Koh, Neil Walkinshaw, Donghwan Shin:
Detecting Multiple Semantic Concerns in Tangled Code Commits. CoRR abs/2601.21298 (2026) - [i24]Ruizhen Gu, José Miguel Rojas, Donghwan Shin:
Automated Testing of Prevalent 3D User Interactions in Virtual Reality Applications. CoRR abs/2601.23139 (2026) - [i23]Zahra G. Yazdi, Van-Hoang Le, Nyyti Saarimäki, Donghwan Shin, Domenico Bianculli, Lionel C. Briand:
Cleaning Logs for Downstream Tasks (Registered Report). CoRR abs/2606.27000 (2026) - [i22]Ruizhen Gu, Konstantinos Koufos, Donghwan Shin, Vahid Garousi, Mehrdad Dianati:
Collaborative Multi-Agent Testing for Emergent Failure Discovery in Autonomous Driving Systems. CoRR abs/2607.06078 (2026) - 2025
- [j16]Ruizhen Gu, José Miguel Rojas, Donghwan Shin:
Software testing for extended reality applications: a systematic mapping study. Autom. Softw. Eng. 32(2): 56 (2025) - [c31]Ruizhen Gu, Jingqiong Zhang, José Miguel Rojas, Donghwan Shin:
On the Promises and Challenges of AI-Powered XR Glasses as Embodied Software. AIware 2025: 207-212 - [c30]Michael Foster, Robert M. Hierons, Donghwan Shin, Neil Walkinshaw, Christopher Wild:
Using Causal Inference to Test Systems with Hidden and Interacting Variables: An Evaluative Case Study. EASE 2025: 592-603 - [c29]Olek Osikowicz, Phil McMinn, Donghwan Shin:
Empirically Evaluating Flaky Tests for Autonomous Driving Systems in Simulated Environments. FTW@ICSE 2025: 13-20 - [c28]Ruizhen Gu, José Miguel Rojas, Donghwan Shin:
Can Test Generation and Program Repair Inform Automated Assessment of Programming Projects? ICST 2025: 699-710 - [c27]Sang In Lee, Donghwan Shin, Jihun Park:
Unseen Data Detection using Routing Entropy in Mixture-of-Experts for Autonomous Vehicles. ASE 2025: 3866-3870 - [c26]Ruizhen Gu, José Miguel Rojas, Donghwan Shin:
XRintTest: An Automated Framework for User Interaction Testing in Extended Reality Applications. ASE 2025: 4013-4016 - [i21]Ruizhen Gu, José Miguel Rojas, Donghwan Shin:
Software Testing for Extended Reality Applications: A Systematic Mapping Study. CoRR abs/2501.08909 (2025) - [i20]Michael Foster, Robert M. Hierons, Donghwan Shin, Neil Walkinshaw, Christopher Wild:
Using Causal Inference to Test Systems with Hidden and Interacting Variables: An Evaluative Case Study. CoRR abs/2504.16526 (2025) - 2024
- [j15]Fatemeh Hadadi, Joshua Heneage Dawes, Donghwan Shin, Domenico Bianculli, Lionel C. Briand:
Systematic Evaluation of Deep Learning Models for Log-based Failure Prediction. Empir. Softw. Eng. 29(5): 105 (2024) - [j14]Zanis Ali Khan, Donghwan Shin, Domenico Bianculli, Lionel C. Briand:
Impact of log parsing on deep learning-based anomaly detection. Empir. Softw. Eng. 29(6): 139 (2024) - [j13]Young Min Baek, Esther Cho, Donghwan Shin, Doo-Hwan Bae:
An Extensible Modeling Method Supporting Ontology-Based Scenario Specification and Domain-Specific Extension. Int. J. Softw. Eng. Knowl. Eng. 34(1): 91-162 (2024) - [j12]Yong-Jun Shin, Donghwan Shin, Doo-Hwan Bae:
Virtual Environment Model Generation for CPS Goal Verification using Imitation Learning. ACM Trans. Embed. Comput. Syst. 23(1): 13:1-13:29 (2024) - [j11]Donato Clun, Donghwan Shin, Antonio Filieri, Domenico Bianculli:
Rigorous Assessment of Model Inference Accuracy using Language Cardinality. ACM Trans. Softw. Eng. Methodol. 33(4): 95:1-95:39 (2024) - [c25]Ziyu Li, Donghwan Shin:
Mutation-based Consistency Testing for Evaluating the Code Understanding Capability of LLMs. CAIN 2024: 150-159 - [c24]Marcello Ceci, Nicolas Sannier, Sallam Abualhaija, Donghwan Shin, Domenico Bianculli, Michael Halling:
Toward Automated Compliance Checking of Fund Activities Using Runtime Verification Techniques. FinanSE@ICSE 2024: 19-20 - [c23]Guannan Lou, Donghwan Shin, Neil Walkinshaw, Robert M. Hierons:
Autonomous Driving System Testing: Traffic Density Does Matter. ICTSS 2024: 315-331 - [c22]Donghwan Shin, Sanjeetha Pennada:
Towards Simplification of Failure Scenarios for Machine Learning-Enabled Autonomous Systems. QRS Companion 2024: 1089-1090 - [i19]Ziyu Li, Donghwan Shin:
Mutation-based Consistency Testing for Evaluating the Code Understanding Capability of LLMs. CoRR abs/2401.05940 (2024) - [i18]Wenyu Liang, Pablo R. Baldivieso, Ross Drummond, Donghwan Shin:
Tuning the feedback controller gains is a simple way to improve autonomous driving performance. CoRR abs/2402.05064 (2024) - [i17]Nyyti Saarimäki, Donghwan Shin, Domenico Bianculli:
Taxonomy of Software Log Smells. CoRR abs/2412.09284 (2024) - 2023
- [j10]Matteo Biagiola, Nicolás Cardozo, Donghwan Shin, Foutse Khomh, Andrea Stocco, Vincenzo Riccio:
Summary of the Fourth International Workshop on Deep Learning for Testing and Testing for Deep Learning (DeepTest 2023). ACM SIGSOFT Softw. Eng. Notes 48(4): 39-40 (2023) - [j9]Sepehr Sharifi, Donghwan Shin, Lionel C. Briand, Nathan Aschbacher:
Identifying the Hazard Boundary of ML-Enabled Autonomous Systems Using Cooperative Coevolutionary Search. IEEE Trans. Software Eng. 49(12): 5120-5138 (2023) - [c21]Joshua Heneage Dawes, Donghwan Shin, Domenico Bianculli:
Towards Log Slicing. FASE 2023: 249-259 - [c20]Fitash Ul Haq, Donghwan Shin, Lionel C. Briand:
Many-Objective Reinforcement Learning for Online Testing of DNN-Enabled Systems. ICSE 2023: 1814-1826 - [i16]Sepehr Sharifi, Donghwan Shin, Lionel C. Briand, Nathan Aschbacher:
Identifying the Hazard Boundary of ML-enabled Autonomous Systems Using Cooperative Co-Evolutionary Search. CoRR abs/2301.13807 (2023) - [i15]Fatemeh Hadadi, Joshua Heneage Dawes, Donghwan Shin, Domenico Bianculli, Lionel C. Briand:
Systematic Evaluation of Deep Learning Models for Failure Prediction. CoRR abs/2303.07230 (2023) - [i14]Zanis Ali Khan, Donghwan Shin, Domenico Bianculli, Lionel C. Briand:
Impact of Log Parsing on Log-based Anomaly Detection. CoRR abs/2305.15897 (2023) - 2022
- [j8]Donghwan Shin, Domenico Bianculli, Lionel C. Briand:
PRINS: scalable model inference for component-based system logs. Empir. Softw. Eng. 27(4): 87 (2022) - [j7]Fitash Ul Haq, Donghwan Shin, Shiva Nejati, Lionel C. Briand:
Correction to: Can Offline Testing of Deep Neural Networks Replace Their Online Testing? Empir. Softw. Eng. 27(6): 141 (2022) - [c19]Fitash Ul Haq, Donghwan Shin, Lionel C. Briand:
Efficient Online Testing for DNN-Enabled Systems using Surrogate-Assisted and Many-Objective Optimization. ICSE 2022: 811-822 - [c18]Zanis Ali Khan, Donghwan Shin, Domenico Bianculli, Lionel C. Briand:
Guidelines for Assessing the Accuracy of Log Message Template Identification Techniques. ICSE 2022: 1095-1106 - [d1]Zanis Ali Khan, Donghwan Shin, Domenico Bianculli, Lionel C. Briand:
Replication package for "Guidelines for Assessing the Accuracy of Log Message Template Identification Techniques". Zenodo, 2022
- [i13]Yong-Jun Shin, Donghwan Shin, Doo-Hwan Bae:
Environment Imitation: Data-Driven Environment Model Generation Using Imitation Learning for Efficient CPS Goal Verification. CoRR abs/2204.06799 (2022) - [i12]Young Min Baek, Esther Cho, Donghwan Shin, Doo-Hwan Bae:
Literature Review to Collect Conceptual Variables of Scenario Methods for Establishing a Conceptual Scenario Framework. CoRR abs/2205.08290 (2022) - [i11]Fitash Ul Haq, Donghwan Shin, Lionel C. Briand:
Many-Objective Reinforcement Learning for Online Testing of DNN-Enabled Systems. CoRR abs/2210.15432 (2022) - [i10]Donato Clun, Donghwan Shin, Antonio Filieri, Domenico Bianculli:
Rigorous Assessment of Model Inference Accuracy using Language Cardinality. CoRR abs/2211.16587 (2022) - 2021
- [j6]Fitash Ul Haq, Donghwan Shin, Shiva Nejati, Lionel Claude Briand:
Can Offline Testing of Deep Neural Networks Replace Their Online Testing? Empir. Softw. Eng. 26(5): 90 (2021) - [c17]Markus Borg, Raja Ben Abdessalem, Shiva Nejati, François-Xavier Jegeden, Donghwan Shin:
Digital Twins Are Not Monozygotic - Cross-Replicating ADAS Testing in Two Industry-Grade Automotive Simulators. ICST 2021: 383-393 - [c16]Fitash Ul Haq, Donghwan Shin, Lionel C. Briand, Thomas Stifter, Jun Wang:
Automatic test suite generation for key-points detection DNNs using many-objective search (experience paper). ISSTA 2021: 91-102 - [c15]Salma Messaoudi, Donghwan Shin, Annibale Panichella, Domenico Bianculli, Lionel C. Briand:
Log-based slicing for system-level test cases. ISSTA 2021: 517-528 - [c14]Donghwan Shin, Zanis Ali Khan, Domenico Bianculli, Lionel C. Briand:
A Theoretical Framework for Understanding the Relationship Between Log Parsing and Anomaly Detection. RV 2021: 277-287 - [i9]Fitash Ul Haq, Donghwan Shin, Shiva Nejati, Lionel C. Briand:
Can Offline Testing of Deep Neural Networks Replace Their Online Testing? CoRR abs/2101.11118 (2021) - [i8]Donghwan Shin, Domenico Bianculli, Lionel C. Briand:
PRINS: Scalable Model Inference for Component-based System Logs. CoRR abs/2106.01987 (2021) - 2020
- [c13]Fitash Ul Haq, Donghwan Shin, Shiva Nejati, Lionel C. Briand:
Comparing Offline and Online Testing of Deep Neural Networks: An Autonomous Car Case Study. ICST 2020: 85-95 - [i7]Donghwan Shin, Domenico Bianculli, Lionel C. Briand:
Effective Removal of Operational Log Messages: an Application to Model Inference. CoRR abs/2004.07194 (2020) - [i6]Fitash Ul Haq, Donghwan Shin, Lionel C. Briand, Thomas Stifter, Jun Wang:
Automatic Test Suite Generation for Key-points Detection DNNs Using Many-Objective Search. CoRR abs/2012.06511 (2020) - [i5]Markus Borg, Raja Ben Abdessalem, Shiva Nejati, François-Xavier Jegeden, Donghwan Shin:
Digital Twins Are Not Monozygotic - Cross-Replicating ADAS Testing in Two Industry-Grade Automotive Simulators. CoRR abs/2012.06822 (2020)
2010 – 2019
- 2019
- [j5]Donghwan Shin, Shin Yoo, Mike Papadakis, Doo-Hwan Bae:
Empirical evaluation of mutation-based test case prioritization techniques. Softw. Test. Verification Reliab. 29(1-2) (2019) - [i4]Donghwan Shin, Salma Messaoudi, Domenico Bianculli, Annibale Panichella, Lionel C. Briand, Raimondas Sasnauskas:
Scalable Inference of System-level Models from Component Logs. CoRR abs/1908.02329 (2019) - [i3]Fitash Ul Haq, Donghwan Shin, Shiva Nejati, Lionel C. Briand:
Comparing Offline and Online Testing of Deep Neural Networks: An Autonomous Car Case Study. CoRR abs/1912.00805 (2019) - 2018
- [j4]Donghwan Shin, Shin Yoo, Doo-Hwan Bae:
A Theoretical and Empirical Study of Diversity-Aware Mutation Adequacy Criterion. IEEE Trans. Software Eng. 44(10): 914-931 (2018) - [c12]Mike Papadakis, Donghwan Shin, Shin Yoo, Doo-Hwan Bae:
Are mutation scores correlated with real fault detection?: a large scale empirical study on the relationship between mutants and real faults. ICSE 2018: 537-548 - [c11]Mingyu Jin, Donghwan Shin, Doo-Hwan Bae:
ABC+: extended action-benefit-cost modeling with knowledge-based decision-making and interaction model for system of systems simulation. SAC 2018: 1698-1701 - 2017
- [c10]Wonkyung Yun, Donghwan Shin, Doo-Hwan Bae:
Mutation Analysis for System of Systems Policy Testing. SESoS/WDES 2017: 16-22 - [i2]Donghwan Shin, Shin Yoo, Mike Papadakis, Doo-Hwan Bae:
Empirical Evaluation of Mutation-based Test Prioritization Techniques. CoRR abs/1709.04631 (2017) - 2016
- [j3]Donghwan Shin, Eunkyoung Jee, Doo-Hwan Bae:
Comprehensive analysis of FBD test coverage criteria using mutants. Softw. Syst. Model. 15(3): 631-645 (2016) - [c9]Yoo Jin Lim, Gwangui Hong, Donghwan Shin, Eunkyoung Jee, Doo-Hwan Bae:
A runtime verification framework for dynamically adaptive multi-agent systems. BigComp 2016: 509-512 - [c8]Dongwon Seo, Donghwan Shin, Young Min Baek, Jiyoung Song, Wonkyung Yun, Junho Kim, Eunkyoung Jee, Doo-Hwan Bae:
Modeling and verification for different types of system of systems using PRISM. SESoS 2016: 12-18 - [c7]Donghwan Shin, Shin Yoo, Doo-Hwan Bae:
Diversity-Aware Mutation Adequacy Criterion for Improving Fault Detection Capability. ICST Workshops 2016: 122-131 - [c6]Donghwan Shin, Doo-Hwan Bae:
A Theoretical Framework for Understanding Mutation-Based Testing Methods. ICST 2016: 299-308 - [i1]Donghwan Shin, Doo-Hwan Bae:
A Theoretical Framework for Understanding Mutation-Based Testing Methods. CoRR abs/1601.06466 (2016) - 2015
- [j2]Jihun Park, Dongwon Seo, Gwangui Hong, Donghwan Shin, Jimin Hwa, Doo-Hwan Bae:
Human Resource Allocation in Software Project with Practical Considerations. Int. J. Softw. Eng. Knowl. Eng. 25(1): 5-26 (2015) - [c5]Dongwon Seo, Donghwan Shin, Doo-Hwan Bae:
Quality Based Software Project Staffing and Scheduling with Budget and Deadline. QuASoQ/WAWSE/CMCE@APSEC 2015: 58 - [c4]Dongwon Seo, Donghwan Shin, Doo-Hwan Bae:
Quality Based Software Project Staffing and Scheduling with Cost Bound. APSEC 2015: 269-276 - [c3]Yoo Jin Lim, Eunkyoung Jee, Donghwan Shin, Doo-Hwan Bae:
Efficient Testing of Self-Adaptive Behaviors in Collective Adaptive Systems. COMPSAC 2015: 216-221 - 2014
- [j1]Eunkyoung Jee, Donghwan Shin, Sung Deok Cha, Jang-Soo Lee, Doo-Hwan Bae:
Automated test case generation for FBD programs implementing reactor protection system software. Softw. Test. Verification Reliab. 24(8): 608-628 (2014) - [c2]Jihun Park, Dongwon Seo, Gwangui Hong, Donghwan Shin, Jimin Hwa, Doo-Hwan Bae:
Practical Human Resource Allocation in Software Projects Using Genetic Algorithm. SEKE 2014: 688-694 - 2012
- [c1]Donghwan Shin, Eunkyoung Jee, Doo-Hwan Bae:
Empirical Evaluation on FBD Model-Based Test Coverage Criteria Using Mutation Analysis. MoDELS 2012: 465-479
Coauthor Index
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