An empirical study on the evolution of test smell. - Dong Jae Kim (ICSE (Companion Volume), 2020)

Studying Test Annotation Maintenance in the Wild. - Dong Jae Kim; Nikolaos Tsantalis; Tse-Hsun Peter Chen; Jinqiu Yang 001 (ICSE, 2021)

How disabled tests manifest in test maintainability challenges? - Dong Jae Kim; Bo Yang; Jinqiu Yang 001; Tse-Hsun (Peter) Chen (ESEC/SIGSOFT FSE, 2021)

The secret life of test smells - an empirical study on test smell evolution and maintenance. - Dong Jae Kim; Tse-Hsun (Peter) Chen; Jinqiu Yang 001 (Empir. Softw. Eng., 2021)

An Empirical Study on Performance Bugs in Deep Learning Frameworks. - Tarek Makkouk; Dong Jae Kim; Tse-Hsun Peter Chen (ICSME, 2022)

Challenges in Adopting Artificial Intelligence Based User Input Verification Framework in Reporting Software Systems. - Dong Jae Kim; Steven Locke; Tse-Hsun Peter Chen; Andrei Toma; Steve Sporea; Laura Weinkam; Sarah Sajedi (ICSE-SEIP, 2023)

A First Look at the Inheritance-Induced Redundant Test Execution. - Dong Jae Kim; Jinqiu Yang 001; Tse-Hsun Chen (ICSE, 2024)

Exploring the Impact of Inheritance on Test Code Maintainability. - Dong Jae Kim; Tse-Hsun Chen (ICSE Companion, 2024)

LLMParser: An Exploratory Study on Using Large Language Models for Log Parsing. - Zeyang Ma; An Ran Chen; Dong Jae Kim; Tse-Hsun Chen; Shaowei Wang 002 (ICSE, 2024)

Blessing or Curse? Investigating Test Code Maintenance Through Inheritance and Interface. - Dong Jae Kim; Tse-Hsun Peter Chen (ICSME, 2024)

Decoding Anomalies! Unraveling Operational Challenges in Human-in-the-Loop Anomaly Validation. - Dong Jae Kim; Steven Locke; Tse-Hsun (Peter) Chen; Andrei Toma; Sarah Sajedi; Steve Sporea; Laura Weinkam (SIGSOFT FSE Companion, 2024)

When LLM-based Code Generation Meets the Software Development Process. - Feng Lin; Dong Jae Kim; Tse-Hsun Chen (CoRR, 2024)

Identifying Performance-Sensitive Configurations in Software Systems through Code Analysis with LLM Agents. - Zehao Wang; Dong Jae Kim; Tse-Hsun Chen (CoRR, 2024)

OpenLogParser: Unsupervised Parsing with Open-Source Large Language Models. - Zeyang Ma; Dong Jae Kim; Tse-Hsun Chen (CoRR, 2024)

Enhancing Fault Localization Through Ordered Code Analysis with LLM Agents and Self-Reflection. - Md Nakhla Rafi; Dong Jae Kim; Tse-Hsun Chen; Shaowei Wang 002 (CoRR, 2024)

Studying and Benchmarking Large Language Models For Log Level Suggestion. - Yi Wen Heng; Zeyang Ma; Zhenhao Li 002; Dong Jae Kim; Tse-Hsun Chen (CoRR, 2024)

The Impact of Input Order Bias on Large Language Models for Software Fault Localization. - Md Nakhla Rafi; Dong Jae Kim; Tse-Hsun Chen; Shaowei Wang 002 (CoRR, 2024)

Towards Better Graph Neural Network-Based Fault Localization through Enhanced Code Representation. - Md Nakhla Rafi; Dong Jae Kim; An Ran Chen; Tse-Hsun (Peter) Chen; Shaowei Wang 002 (Proc. ACM Softw. Eng., 2024)

SOEN-101: Code Generation by Emulating Software Process Models Using Large Language Model Agents. - Feng Lin; Dong Jae Kim; Tse-Hsun Chen (ICSE, 2025)

LibreLog: Accurate and Efficient Unsupervised Log Parsing Using Open-Source Large Language Models. - Zeyang Ma; Dong Jae Kim; Tse-Hsun Peter Chen (ICSE, 2025)

Benchmarking Open-Source Large Language Models for Log Level Suggestion. - Yi Wen Heng; Zeyang Ma; Zhenhao Li 002; Dong Jae Kim; Tse-Hsun Chen (ICST, 2025)

RobuNFR: Evaluating the Robustness of Large Language Models on Non-Functional Requirements Aware Code Generation. - Feng Lin; Dong Jae Kim; Zhenhao Li 002; Jinqiu Yang 001; Tse-Hsun (Peter) Chen (CoRR, 2025)