Thanh Trong Vu

dblp:330/0979 · DBLP profile ↗
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6ranked-venue papers
3as first author
6since 2021 · last 2026
0009-0008-3377-6565ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 6 · 3 first-author · 6 since 2021
YearPublicationVenuePosition
2026 Model-agnostic quality assessment for LLM-generated code via dynamic internal representation selection
Thanh Trong Vu, Tuan-Dung Bui, Thu-Trang Nguyen, Hieu Dinh Vo
J. Syst. Softw.1
2025 An empirical study on capability of Large Language Models in understanding code semantics
Thu-Trang Nguyen, Thanh Trong Vu, Hieu Dinh Vo
Inf. Softw. Technol.2
2025 Automated description generation for software patches
Thanh Trong Vu, Tuan-Dung Bui, Thanh-Dat Do, Thu-Trang Nguyen, Hieu Dinh Vo
Inf. Softw. Technol.1
2025 Correctness assessment of code generated by Large Language Models using internal representations
Tuan-Dung Bui, Thanh Trong Vu, Thu-Trang Nguyen, Hieu Dinh Vo
J. Syst. Softw.2
2024 Context-Encoded Code Change Representation for Automated Commit Message Generation
abstract
Changes in source code are an inevitable part of software development. They are the results of indispensable activities such as fixing bugs or improving functionality. Descriptions for code changes (commit messages) help people better understand the changes. However, due to the lack of motivation and time pressure, writing high-quality commit messages remains reluctantly considered. Several methods have been proposed with the aim of automated commit message generation. However, the existing methods are still limited because they only utilize either the changed codes or the changed codes combined with their surrounding statements. This paper proposes a method to represent code changes by combining the changed codes and the unchanged codes which have program dependence on the changed codes. Specifically, we first create program dependence graphs (PDGs) of source code before and after the change. After that, slices related to the changed code from these PDGs are extracted. These slices are then merged to represent the change. This method overcomes the limitations of current representations while improving the performance of 5/6 of state-of-the-art commit message generation methods by up to 15% in METEOR, 14% in ROUGE-L, and 10% in BLEU-4.
Thanh Trong Vu, Thanh-Dat Do, Hieu Dinh Vo
Int. J. Softw. Eng. Knowl. Eng.1
2024 Code-centric learning-based just-in-time vulnerability detection
Thu-Trang Nguyen, Thanh Trong Vu, Thanh-Dat Do, Kien-Tuan Ngo, Hieu Dinh Vo
J. Syst. Softw.3