Donghwan Shin - RankMe

70 papers A* 5A 8B 4C 3Misc 1Journal 40Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Systematic Mapping Study on the Debugging of Autonomous Driving Systems. CoRR Nathan Shaw, Sanjeetha Pennada, Robert M. Hierons, Donghwan Shin
2026	J	`jnl`	Automated Testing of Prevalent 3D User Interactions in Virtual Reality Applications. CoRR Ruizhen Gu, José Miguel Rojas, Donghwan Shin
2026	J	`jnl`	Detecting Multiple Semantic Concerns in Tangled Code Commits. CoRR Beomsu Koh, Neil Walkinshaw, Donghwan Shin
2025	A	`conf`	Can Test Generation and Program Repair Inform Automated Assessment of Programming Projects? ICST Ruizhen Gu, José Miguel Rojas, Donghwan Shin
2025	—	`conf`	Empirically Evaluating Flaky Tests for Autonomous Driving Systems in Simulated Environments. FTW@ICSE Olek Osikowicz, Phil McMinn, Donghwan Shin
2025	—	`conf`	On the Promises and Challenges of AI-Powered XR Glasses as Embodied Software. AIware Ruizhen Gu, Jingqiong Zhang, José Miguel Rojas, Donghwan Shin
2025	J	`jnl`	Software Testing for Extended Reality Applications: A Systematic Mapping Study. CoRR Ruizhen Gu, José Miguel Rojas, Donghwan Shin
2025	J	`jnl`	Software testing for extended reality applications: a systematic mapping study. Autom. Softw. Eng. Ruizhen Gu, José Miguel Rojas, Donghwan Shin
2025	A	`conf`	Using Causal Inference to Test Systems with Hidden and Interacting Variables: An Evaluative Case Study. EASE Michael Foster, Robert M. Hierons, Donghwan Shin, Neil Walkinshaw, Christopher Wild
2025	J	`jnl`	Using Causal Inference to Test Systems with Hidden and Interacting Variables: An Evaluative Case Study. CoRR Michael Foster, Robert M. Hierons, Donghwan Shin, Neil Walkinshaw, Christopher Wild
2025	A*	`conf`	XRintTest: An Automated Framework for User Interaction Testing in Extended Reality Applications. ASE Ruizhen Gu, José Miguel Rojas, Donghwan Shin
2024	J	`jnl`	An Extensible Modeling Method Supporting Ontology-Based Scenario Specification and Domain-Specific Extension. Int. J. Softw. Eng. Knowl. Eng. Young Min Baek, Esther Cho, Donghwan Shin, Doo-Hwan Bae
2024	C	`conf`	Autonomous Driving System Testing: Traffic Density Does Matter. ICTSS Guannan Lou, Donghwan Shin, Neil Walkinshaw, Robert M. Hierons
2024	J	`jnl`	Impact of log parsing on deep learning-based anomaly detection. Empir. Softw. Eng. Zanis Ali Khan, Donghwan Shin, Domenico Bianculli, Lionel C. Briand
2024	B	`conf`	Mutation-based Consistency Testing for Evaluating the Code Understanding Capability of LLMs. CAIN Ziyu Li, Donghwan Shin
2024	J	`jnl`	Mutation-based Consistency Testing for Evaluating the Code Understanding Capability of LLMs. CoRR Ziyu Li, Donghwan Shin
2024	J	`jnl`	Rigorous Assessment of Model Inference Accuracy using Language Cardinality. ACM Trans. Softw. Eng. Methodol. Donato Clun, Donghwan Shin, Antonio Filieri, Domenico Bianculli
2024	J	`jnl`	Systematic Evaluation of Deep Learning Models for Log-based Failure Prediction. Empir. Softw. Eng. Fatemeh Hadadi, Joshua Heneage Dawes, Donghwan Shin, Domenico Bianculli, Lionel C. Briand
2024	J	`jnl`	Taxonomy of Software Log Smells. CoRR Nyyti Saarimäki, Donghwan Shin, Domenico Bianculli
2024	—	`conf`	Toward Automated Compliance Checking of Fund Activities Using Runtime Verification Techniques. FinanSE@ICSE Marcello Ceci, Nicolas Sannier, Sallam Abualhaija, Donghwan Shin, Domenico Bianculli, Michael Halling
2024	—	`conf`	Towards Simplification of Failure Scenarios for Machine Learning-Enabled Autonomous Systems. QRS Companion Donghwan Shin, Sanjeetha Pennada
2024	J	`jnl`	Tuning the feedback controller gains is a simple way to improve autonomous driving performance. CoRR Wenyu Liang, Pablo R. Baldivieso, Ross Drummond, Donghwan Shin
2024	J	`jnl`	Virtual Environment Model Generation for CPS Goal Verification using Imitation Learning. ACM Trans. Embed. Comput. Syst. Yong-Jun Shin, Donghwan Shin, Doo-Hwan Bae
2023	J	`jnl`	Identifying the Hazard Boundary of ML-Enabled Autonomous Systems Using Cooperative Coevolutionary Search. IEEE Trans. Software Eng. Sepehr Sharifi, Donghwan Shin, Lionel C. Briand, Nathan Aschbacher
2023	J	`jnl`	Identifying the Hazard Boundary of ML-enabled Autonomous Systems Using Cooperative Co-Evolutionary Search. CoRR Sepehr Sharifi, Donghwan Shin, Lionel C. Briand, Nathan Aschbacher
2023	J	`jnl`	Impact of Log Parsing on Log-based Anomaly Detection. CoRR Zanis Ali Khan, Donghwan Shin, Domenico Bianculli, Lionel C. Briand
2023	A*	`conf`	Many-Objective Reinforcement Learning for Online Testing of DNN-Enabled Systems. ICSE Fitash Ul Haq, Donghwan Shin, Lionel C. Briand
2023	J	`jnl`	Summary of the Fourth International Workshop on Deep Learning for Testing and Testing for Deep Learning (DeepTest 2023). ACM SIGSOFT Softw. Eng. Notes Matteo Biagiola, Nicolás Cardozo, Donghwan Shin, Foutse Khomh, Andrea Stocco, Vincenzo Riccio
2023	J	`jnl`	Systematic Evaluation of Deep Learning Models for Failure Prediction. CoRR Fatemeh Hadadi, Joshua Heneage Dawes, Donghwan Shin, Domenico Bianculli, Lionel C. Briand
2023	B	`conf`	Towards Log Slicing. FASE Joshua Heneage Dawes, Donghwan Shin, Domenico Bianculli
2022	J	`jnl`	Correction to: Can Offline Testing of Deep Neural Networks Replace Their Online Testing? Empir. Softw. Eng. Fitash Ul Haq, Donghwan Shin, Shiva Nejati, Lionel C. Briand
2022	A*	`conf`	Efficient Online Testing for DNN-Enabled Systems using Surrogate-Assisted and Many-Objective Optimization. ICSE Fitash Ul Haq, Donghwan Shin, Lionel C. Briand
2022	J	`jnl`	Environment Imitation: Data-Driven Environment Model Generation Using Imitation Learning for Efficient CPS Goal Verification. CoRR Yong-Jun Shin, Donghwan Shin, Doo-Hwan Bae
2022	A*	`conf`	Guidelines for Assessing the Accuracy of Log Message Template Identification Techniques. ICSE Zanis Ali Khan, Donghwan Shin, Domenico Bianculli, Lionel C. Briand
2022	J	`jnl`	Literature Review to Collect Conceptual Variables of Scenario Methods for Establishing a Conceptual Scenario Framework. CoRR Young Min Baek, Esther Cho, Donghwan Shin, Doo-Hwan Bae
2022	J	`jnl`	Many-Objective Reinforcement Learning for Online Testing of DNN-Enabled Systems. CoRR Fitash Ul Haq, Donghwan Shin, Lionel C. Briand
2022	J	`jnl`	PRINS: scalable model inference for component-based system logs. Empir. Softw. Eng. Donghwan Shin, Domenico Bianculli, Lionel C. Briand
2022	J	`jnl`	Rigorous Assessment of Model Inference Accuracy using Language Cardinality. CoRR Donato Clun, Donghwan Shin, Antonio Filieri, Domenico Bianculli
2021	B	`conf`	A Theoretical Framework for Understanding the Relationship Between Log Parsing and Anomaly Detection. RV Donghwan Shin, Zanis Ali Khan, Domenico Bianculli, Lionel C. Briand
2021	A	`conf`	Automatic test suite generation for key-points detection DNNs using many-objective search (experience paper). ISSTA Fitash Ul Haq, Donghwan Shin, Lionel C. Briand, Thomas Stifter, Jun Wang
2021	J	`jnl`	Can Offline Testing of Deep Neural Networks Replace Their Online Testing? CoRR Fitash Ul Haq, Donghwan Shin, Shiva Nejati, Lionel C. Briand
2021	J	`jnl`	Can Offline Testing of Deep Neural Networks Replace Their Online Testing? Empir. Softw. Eng. Fitash Ul Haq, Donghwan Shin, Shiva Nejati, Lionel Claude Briand
2021	A	`conf`	Digital Twins Are Not Monozygotic - Cross-Replicating ADAS Testing in Two Industry-Grade Automotive Simulators. ICST Markus Borg, Raja Ben Abdessalem, Shiva Nejati, François-Xavier Jegeden, Donghwan Shin
2021	A	`conf`	Log-based slicing for system-level test cases. ISSTA Salma Messaoudi, Donghwan Shin, Annibale Panichella, Domenico Bianculli, Lionel C. Briand
2021	J	`jnl`	PRINS: Scalable Model Inference for Component-based System Logs. CoRR Donghwan Shin, Domenico Bianculli, Lionel C. Briand
2020	J	`jnl`	Automatic Test Suite Generation for Key-points Detection DNNs Using Many-Objective Search. CoRR Fitash Ul Haq, Donghwan Shin, Lionel C. Briand, Thomas Stifter, Jun Wang
2020	A	`conf`	Comparing Offline and Online Testing of Deep Neural Networks: An Autonomous Car Case Study. ICST Fitash Ul Haq, Donghwan Shin, Shiva Nejati, Lionel C. Briand
2020	J	`jnl`	Digital Twins Are Not Monozygotic - Cross-Replicating ADAS Testing in Two Industry-Grade Automotive Simulators. CoRR Markus Borg, Raja Ben Abdessalem, Shiva Nejati, François-Xavier Jegeden, Donghwan Shin
2020	J	`jnl`	Effective Removal of Operational Log Messages: an Application to Model Inference. CoRR Donghwan Shin, Domenico Bianculli, Lionel C. Briand
2019	J	`jnl`	Comparing Offline and Online Testing of Deep Neural Networks: An Autonomous Car Case Study. CoRR Fitash Ul Haq, Donghwan Shin, Shiva Nejati, Lionel C. Briand
2019	J	`jnl`	Empirical evaluation of mutation-based test case prioritization techniques. Softw. Test. Verification Reliab. Donghwan Shin, Shin Yoo, Mike Papadakis, Doo-Hwan Bae
2019	J	`jnl`	Scalable Inference of System-level Models from Component Logs. CoRR Donghwan Shin, Salma Messaoudi, Domenico Bianculli, Annibale Panichella, Lionel C. Briand, Raimondas Sasnauskas
2018	J	`jnl`	A Theoretical and Empirical Study of Diversity-Aware Mutation Adequacy Criterion. IEEE Trans. Software Eng. Donghwan Shin, Shin Yoo, Doo-Hwan Bae
2018	Misc	`conf`	ABC SAC Mingyu Jin, Donghwan Shin, Doo-Hwan Bae
2018	A*	`conf`	Are mutation scores correlated with real fault detection?: a large scale empirical study on the relationship between mutants and real faults. ICSE Mike Papadakis, Donghwan Shin, Shin Yoo, Doo-Hwan Bae
2017	J	`jnl`	Empirical Evaluation of Mutation-based Test Prioritization Techniques. CoRR Donghwan Shin, Shin Yoo, Mike Papadakis, Doo-Hwan Bae
2017	—	`conf`	Mutation Analysis for System of Systems Policy Testing. SESoS/WDES Wonkyung Yun, Donghwan Shin, Doo-Hwan Bae
2016	A	`conf`	A Theoretical Framework for Understanding Mutation-Based Testing Methods. ICST Donghwan Shin, Doo-Hwan Bae
2016	J	`jnl`	A Theoretical Framework for Understanding Mutation-Based Testing Methods. CoRR Donghwan Shin, Doo-Hwan Bae
2016	—	`conf`	A runtime verification framework for dynamically adaptive multi-agent systems. BigComp Yoo Jin Lim, Gwangui Hong, Donghwan Shin, Eunkyoung Jee, Doo-Hwan Bae
2016	J	`jnl`	Comprehensive analysis of FBD test coverage criteria using mutants. Softw. Syst. Model. Donghwan Shin, Eunkyoung Jee, Doo-Hwan Bae
2016	—	`conf`	Diversity-Aware Mutation Adequacy Criterion for Improving Fault Detection Capability. ICST Workshops Donghwan Shin, Shin Yoo, Doo-Hwan Bae
2016	—	`conf`	Modeling and verification for different types of system of systems using PRISM. SESoS Dongwon Seo, Donghwan Shin, Young Min Baek, Jiyoung Song, Wonkyung Yun, Junho Kim, Eunkyoung Jee, Doo-Hwan Bae
2015	B	`conf`	Efficient Testing of Self-Adaptive Behaviors in Collective Adaptive Systems. COMPSAC Yoo Jin Lim, Eunkyoung Jee, Donghwan Shin, Doo-Hwan Bae
2015	J	`jnl`	Human Resource Allocation in Software Project with Practical Considerations. Int. J. Softw. Eng. Knowl. Eng. Jihun Park, Dongwon Seo, Gwangui Hong, Donghwan Shin, Jimin Hwa, Doo-Hwan Bae
2015	—	`conf`	Quality Based Software Project Staffing and Scheduling with Budget and Deadline. QuASoQ/WAWSE/CMCE@APSEC Dongwon Seo, Donghwan Shin, Doo-Hwan Bae
2015	C	`conf`	Quality Based Software Project Staffing and Scheduling with Cost Bound. APSEC Dongwon Seo, Donghwan Shin, Doo-Hwan Bae
2014	J	`jnl`	Automated test case generation for FBD programs implementing reactor protection system software. Softw. Test. Verification Reliab. Eunkyoung Jee, Donghwan Shin, Sung Deok Cha, Jang-Soo Lee, Doo-Hwan Bae
2014	C	`conf`	Practical Human Resource Allocation in Software Projects Using Genetic Algorithm. SEKE Jihun Park, Dongwon Seo, Gwangui Hong, Donghwan Shin, Jimin Hwa, Doo-Hwan Bae
2012	A	`conf`	Empirical Evaluation on FBD Model-Based Test Coverage Criteria Using Mutation Analysis. MoDELS Donghwan Shin, Eunkyoung Jee, Doo-Hwan Bae