Empirical Evaluation on FBD Model-Based Test Coverage Criteria Using Mutation Analysis. - Donghwan Shin 001; Eunkyoung Jee; Doo-Hwan Bae (MoDELS, 2012)

Practical Human Resource Allocation in Software Projects Using Genetic Algorithm. - Jihun Park; Dongwon Seo; Gwangui Hong; Donghwan Shin 001; Jimin Hwa; Doo-Hwan Bae (SEKE, 2014)

Automated test case generation for FBD programs implementing reactor protection system software. - Eunkyoung Jee; Donghwan Shin 001; Sung Deok Cha; Jang-Soo Lee; Doo-Hwan Bae (Softw. Test. Verification Reliab., 2014)

Quality Based Software Project Staffing and Scheduling with Budget and Deadline. - Dongwon Seo; Donghwan Shin 001; Doo-Hwan Bae (QuASoQ/WAWSE/CMCE@APSEC, 2015)

Quality Based Software Project Staffing and Scheduling with Cost Bound. - Dongwon Seo; Donghwan Shin 001; Doo-Hwan Bae (APSEC, 2015)

Efficient Testing of Self-Adaptive Behaviors in Collective Adaptive Systems. - Yoo Jin Lim; Eunkyoung Jee; Donghwan Shin 001; Doo-Hwan Bae (COMPSAC, 2015)

Human Resource Allocation in Software Project with Practical Considerations. - Jihun Park; Dongwon Seo; Gwangui Hong; Donghwan Shin 001; Jimin Hwa; Doo-Hwan Bae (Int. J. Softw. Eng. Knowl. Eng., 2015)

A runtime verification framework for dynamically adaptive multi-agent systems. - Yoo Jin Lim; Gwangui Hong; Donghwan Shin 001; Eunkyoung Jee; Doo-Hwan Bae (BigComp, 2016)

Modeling and verification for different types of system of systems using PRISM. - Dongwon Seo; Donghwan Shin 001; Young Min Baek; Jiyoung Song; Wonkyung Yun; Junho Kim; Eunkyoung Jee; Doo-Hwan Bae (SESoS, 2016)

A Theoretical Framework for Understanding Mutation-Based Testing Methods. - Donghwan Shin 001; Doo-Hwan Bae (ICST, 2016)

Diversity-Aware Mutation Adequacy Criterion for Improving Fault Detection Capability. - Donghwan Shin 001; Shin Yoo; Doo-Hwan Bae (ICST Workshops, 2016)

Comprehensive analysis of FBD test coverage criteria using mutants. - Donghwan Shin 001; Eunkyoung Jee; Doo-Hwan Bae (Softw. Syst. Model., 2016)

Mutation Analysis for System of Systems Policy Testing. - Wonkyung Yun; Donghwan Shin 001; Doo-Hwan Bae (SESoS/WDES, 2017)

Empirical Evaluation of Mutation-based Test Prioritization Techniques. - Donghwan Shin 001; Shin Yoo; Mike Papadakis; Doo-Hwan Bae (CoRR, 2017)

Are mutation scores correlated with real fault detection?: a large scale empirical study on the relationship between mutants and real faults. - Mike Papadakis; Donghwan Shin 001; Shin Yoo; Doo-Hwan Bae (ICSE, 2018)

ABC+: extended action-benefit-cost modeling with knowledge-based decision-making and interaction model for system of systems simulation. - Mingyu Jin; Donghwan Shin 001; Doo-Hwan Bae (SAC, 2018)

A Theoretical and Empirical Study of Diversity-Aware Mutation Adequacy Criterion. - Donghwan Shin 001; Shin Yoo; Doo-Hwan Bae (IEEE Trans. Software Eng., 2018)

Scalable Inference of System-level Models from Component Logs. - Donghwan Shin 001; Salma Messaoudi; Domenico Bianculli; Annibale Panichella; Lionel C. Briand; Raimondas Sasnauskas (CoRR, 2019)

Empirical evaluation of mutation-based test case prioritization techniques. - Donghwan Shin 001; Shin Yoo; Mike Papadakis; Doo-Hwan Bae (Softw. Test. Verification Reliab., 2019)

Comparing Offline and Online Testing of Deep Neural Networks: An Autonomous Car Case Study. - Fitash Ul Haq; Donghwan Shin 001; Shiva Nejati 001; Lionel C. Briand (ICST, 2020)

Effective Removal of Operational Log Messages: an Application to Model Inference. - Donghwan Shin 001; Domenico Bianculli; Lionel C. Briand (CoRR, 2020)

Automatic Test Suite Generation for Key-points Detection DNNs Using Many-Objective Search. - Fitash Ul Haq; Donghwan Shin 001; Lionel C. Briand; Thomas Stifter; Jun Wang 020 (CoRR, 2020)

Digital Twins Are Not Monozygotic - Cross-Replicating ADAS Testing in Two Industry-Grade Automotive Simulators. - Markus Borg; Raja Ben Abdessalem; Shiva Nejati 001; François-Xavier Jegeden; Donghwan Shin 001 (ICST, 2021)

Automatic test suite generation for key-points detection DNNs using many-objective search (experience paper). - Fitash Ul Haq; Donghwan Shin 001; Lionel C. Briand; Thomas Stifter; Jun Wang 020 (ISSTA, 2021)

Log-based slicing for system-level test cases. - Salma Messaoudi; Donghwan Shin 001; Annibale Panichella; Domenico Bianculli; Lionel C. Briand (ISSTA, 2021)

A Theoretical Framework for Understanding the Relationship Between Log Parsing and Anomaly Detection. - Donghwan Shin 001; Zanis Ali Khan; Domenico Bianculli; Lionel C. Briand (RV, 2021)

Can Offline Testing of Deep Neural Networks Replace Their Online Testing? - Fitash Ul Haq; Donghwan Shin 001; Shiva Nejati 001; Lionel Claude Briand (Empir. Softw. Eng., 2021)

Efficient Online Testing for DNN-Enabled Systems using Surrogate-Assisted and Many-Objective Optimization. - Fitash Ul Haq; Donghwan Shin 001; Lionel C. Briand (ICSE, 2022)

Guidelines for Assessing the Accuracy of Log Message Template Identification Techniques. - Zanis Ali Khan; Donghwan Shin 001; Domenico Bianculli; Lionel C. Briand (ICSE, 2022)

Environment Imitation: Data-Driven Environment Model Generation Using Imitation Learning for Efficient CPS Goal Verification. - Yong-Jun Shin; Donghwan Shin 001; Doo-Hwan Bae (CoRR, 2022)

Literature Review to Collect Conceptual Variables of Scenario Methods for Establishing a Conceptual Scenario Framework. - Young Min Baek; Esther Cho; Donghwan Shin 001; Doo-Hwan Bae (CoRR, 2022)

Correction to: Can Offline Testing of Deep Neural Networks Replace Their Online Testing? - Fitash Ul Haq; Donghwan Shin 001; Shiva Nejati 001; Lionel C. Briand (Empir. Softw. Eng., 2022)

PRINS: scalable model inference for component-based system logs. - Donghwan Shin 001; Domenico Bianculli; Lionel C. Briand (Empir. Softw. Eng., 2022)

Replication package for "Guidelines for Assessing the Accuracy of Log Message Template Identification Techniques". - Zanis Ali Khan; Donghwan Shin 001; Domenico Bianculli; Lionel C. Briand (Zenodo, 2022)

Towards Log Slicing. - Joshua Heneage Dawes; Donghwan Shin 001; Domenico Bianculli (FASE, 2023)

Many-Objective Reinforcement Learning for Online Testing of DNN-Enabled Systems. - Fitash Ul Haq; Donghwan Shin 001; Lionel C. Briand (ICSE, 2023)

Identifying the Hazard Boundary of ML-enabled Autonomous Systems Using Cooperative Co-Evolutionary Search. - Sepehr Sharifi; Donghwan Shin 001; Lionel C. Briand; Nathan Aschbacher (CoRR, 2023)

Systematic Evaluation of Deep Learning Models for Failure Prediction. - Fatemeh Hadadi; Joshua Heneage Dawes; Donghwan Shin 001; Domenico Bianculli; Lionel C. Briand (CoRR, 2023)

Impact of Log Parsing on Log-based Anomaly Detection. - Zanis Ali Khan; Donghwan Shin 001; Domenico Bianculli; Lionel C. Briand (CoRR, 2023)

Summary of the Fourth International Workshop on Deep Learning for Testing and Testing for Deep Learning (DeepTest 2023). - Matteo Biagiola; Nicolás Cardozo; Donghwan Shin 001; Foutse Khomh; Andrea Stocco 001; Vincenzo Riccio (ACM SIGSOFT Softw. Eng. Notes, 2023)

Identifying the Hazard Boundary of ML-Enabled Autonomous Systems Using Cooperative Coevolutionary Search. - Sepehr Sharifi; Donghwan Shin 001; Lionel C. Briand; Nathan Aschbacher (IEEE Trans. Software Eng., 2023)

Mutation-based Consistency Testing for Evaluating the Code Understanding Capability of LLMs. - Ziyu Li; Donghwan Shin 001 (CAIN, 2024)

Toward Automated Compliance Checking of Fund Activities Using Runtime Verification Techniques. - Marcello Ceci; Nicolas Sannier; Sallam Abualhaija; Donghwan Shin 001; Domenico Bianculli; Michael Halling (FinanSE@ICSE, 2024)

Autonomous Driving System Testing: Traffic Density Does Matter. - Guannan Lou; Donghwan Shin 001; Neil Walkinshaw; Robert M. Hierons (ICTSS, 2024)

Towards Simplification of Failure Scenarios for Machine Learning-Enabled Autonomous Systems. - Donghwan Shin 001; Sanjeetha Pennada (QRS Companion, 2024)

Tuning the feedback controller gains is a simple way to improve autonomous driving performance. - Wenyu Liang; Pablo R. Baldivieso; Ross Drummond; Donghwan Shin 001 (CoRR, 2024)

Taxonomy of Software Log Smells. - Nyyti Saarimäki; Donghwan Shin 001; Domenico Bianculli (CoRR, 2024)

An Extensible Modeling Method Supporting Ontology-Based Scenario Specification and Domain-Specific Extension. - Young Min Baek; Esther Cho; Donghwan Shin 001; Doo-Hwan Bae (Int. J. Softw. Eng. Knowl. Eng., 2024)

Virtual Environment Model Generation for CPS Goal Verification using Imitation Learning. - Yong-Jun Shin; Donghwan Shin 001; Doo-Hwan Bae (ACM Trans. Embed. Comput. Syst., 2024)

Rigorous Assessment of Model Inference Accuracy using Language Cardinality. - Donato Clun; Donghwan Shin 001; Antonio Filieri; Domenico Bianculli (ACM Trans. Softw. Eng. Methodol., 2024)

Systematic Evaluation of Deep Learning Models for Log-based Failure Prediction. - Fatemeh Hadadi; Joshua Heneage Dawes; Donghwan Shin 001; Domenico Bianculli; Lionel C. Briand (Empir. Softw. Eng., 2024)

Impact of log parsing on deep learning-based anomaly detection. - Zanis Ali Khan; Donghwan Shin 001; Domenico Bianculli; Lionel C. Briand (Empir. Softw. Eng., 2024)

Empirically Evaluating Flaky Tests for Autonomous Driving Systems in Simulated Environments. - Olek Osikowicz; Phil McMinn; Donghwan Shin 001 (FTW@ICSE, 2025)

Can Test Generation and Program Repair Inform Automated Assessment of Programming Projects? - Ruizhen Gu; José Miguel Rojas; Donghwan Shin 001 (ICST, 2025)

Using Causal Inference to Test Systems with Hidden and Interacting Variables: An Evaluative Case Study. - Michael Foster 001; Robert M. Hierons; Donghwan Shin 001; Neil Walkinshaw; Christopher Wild (CoRR, 2025)

Software testing for extended reality applications: a systematic mapping study. - Ruizhen Gu; José Miguel Rojas; Donghwan Shin 001 (Autom. Softw. Eng., 2025)