Publications

ACL

Can LLMs Reason About Program Semantics? A Comprehensive Evaluation of LLMs on Formal Specification Inference

Thanh Le-Cong, Bach Le, Toby Murray

TL;DR: FormalBench: A dataset for benchmarking LLMs' reasoning on program semantics via formal specification inference

The 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025),

ICSME

Toward Realistic Evaluations of Just-In-Time Vulnerability Prediction

Duong Nguyen, Thanh Le-Cong, Triet Huynh Minh Le, M. Ali Babar, Quyet-Thang Huynh

TL;DR: Revisit the effectiveness of Just-In-Time Vulnerability Prediction techniques with realistic evaluation settings.

The 40th IEEE International Conference on Software Maintenance and Evolution (ICSME 2025), Research Track

TOSEM

Towards Reliable Evaluation of Neural Program Repair with Natural Robustness Testing

Thanh Le-Cong, Dat Nguyen, Bach Le, Toby Murray

TL;DR: An empirical study on the robustness of Neural Program Repair techniques against natural semantic-preserving transformations.

ACM Transactions on Software Engineering and Methodology, Just Accepted, 2025

EASE

LEGION: Harnessing Pre-trained Language Models for GitHub Topic Recommendations with Distribution-Balance Loss

Yen-Trang Dang, Thanh Le-Cong, Phuc-Thanh Nguyen, Anh M. T. Bui, Phuong T. Nguyen, Bach Le, and Quyet-Thang Huynh

TL;DR: Investigating and addressing the impact of Long-tailed distribution of GitHub topics on the performance of pre-trained language models for topic recommendation.

International Conference on Evaluation and Assessment in Software Engineering (EASE 2024), Research Track

TSE

Leveraging Large Language Model for Automatic Patch Correctness Assessment

Xin Zhou, Bowen Xu, Kisub Kim, DongGyun Han, Hung Nguyen, Thanh Le-Cong, Junda He, Bach Le, David Lo

TL;DR: Automatic Patch Correctness Assessment in Program Repair with Large Language Models.

IEEE Transactions on Software Engineering, Volume 50, 2024

TOSEM

Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues?

Yue Liu, Thanh Le-Cong, Ratnadira Widyasari, Chakkrit Tantithamthavorn, Li Li, Bach Le, David Lo

TL;DR: An empirical study on code quality issues in ChatGPT-generated code.

ACM Transactions on Software Engineering and Methodology, Volume 33, 2024

TSE

MiDas: Multi-Granularity Detector for Vulnerability Fixes

Truong Giang Nguyen, Thanh Le-Cong, Hong Jin Kang, Ratnadira Widyasari, Chengran Yang, Zhipeng Zhao, Bowen Xu, Jiayuan Zhou, Xin Xia, Ahmed E. Hassan, Bach Le, David Lo

TL;DR: Identifying vulnerability fixes by analyzing multi-granularity of code changes.

IEEE Transactions on Software Engineering, Volume 49, 2023

TSE

Invalidator: Automated Patch Correctness Assessment via Semantic and Syntactic Reasoning

Thanh Le-Cong, Duc-Minh Luong, Bach Le, David Lo, Nhat Hoa Tran, Quang Huy Bui, Quyet Thang Huynh

TL;DR: Reasoning about the correctness of APR-generated patches via program invariants and code representation learning.

IEEE Transactions on Software Engineering, Volume 49, 2023

ICSE

Chronos: Time-Aware Zero-Shot Identification of Libraries from Vulnerability Reports

Yunbo Lyu⁺, Thanh Le-Cong⁺, Hong Jin Kang, Ratnadira Widyasari, Zhao Zhipeng, Bach Le, Ming Li, David Lo

TL;DR: Identifying vulnerable libraries from vulnerability reports via zero-shot learning and domain-specific mechanisms.

45th IEEE/ACM International Conference on Software Engineering (ICSE 2023), Research Track

SANER

Topic Recommendation for GitHub Repositories: How Far Can Extreme Multi-Label Learning Go?

Ratnadira Widyasari, Zhipeng Zhao, Thanh Le Cong, Hong Jin Kang, David Lo

TL;DR: Empirical study on the effectiveness of Extreme Multi-Label Learning and existing techniques for GitHub topic recommendation in a realistic setting.

28th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2023), Research Track

ICSME

FFL: Fine-grained Fault Localization for Student Programs via Syntactic and Semantic Reasoning

Thanh-Dat Nguyen, Thanh Le-Cong, Duc-Minh Luong, Van-Hai Duong, Bach Le, David Lo, Quyet-Thang Huynh

TL;DR: Automatically identifying fault locations in student programs by applying Graph Neural Network on a fine-grained graph-based representation of the program, which combines AST with test coverage information.

The 38th IEEE International Conference on Software Maintenance and Evolution (ICSME 2022), Research Track

FSE

AutoPruner: Transformer-Based Call Graph Pruning

Thanh Le-Cong, Hong Jin Kang, Truong Giang Nguyen, Stefanus Agus Haryono, David Lo, Bach Le, Thang Huynh Quyet

TL;DR: Pruning false positives in static call graph via code features learned by Large Language Model and syntactic features extracted from the original call graph.

ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2022), Research Track

ISSRE

Usability and Aesthetics: Better Together for Automated Repair of Web Pages

Thanh Le-Cong, Bach Le, Quyet-Thang Huynh, Phi Le Nguyen

TL;DR: Automatically repairing mobile-unfriendly web pages using Evolutionary Optimization.

IEEE 32nd International Symposium on Software Reliability Engineering (ISSRE 2021), Research Track