Address: Desk 2.075, Level 2, Melbourne Connect, 700 Swanston St, Carlton, Melbourne, Victoria, Australia
Email: congthanh.le student.unimelb.edu.au
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About Me
I am Thanh Le-Cong (Lê Công Thành in Vietnamese), a second-year Ph.D. student at CIS, The University of Melbourne . During my PhD, I am fortunate to be advised by Dr. Bach Le and Prof. Toby Murray, and supported by Melbourne Research Scholarship and Google PhD Fellowship. Before joining UoM, I worked as a research engineer at SOAR (SOftware Analytic Research), Singapore Management University under the advisor of Prof. David Lo. I was also an applied scientist intern of Automated Reason Group at Amazon Web Services working with Dr. Brandon Paulsen, Dr. Joey Dodds and Prof. Daniel Kroening.
My passion lies in leveraging AI and data mining to tackle real-world challenges in software engineering and pushing the boundaries of programming technologies. My goal to is to build trustworthy AI-powered tools for supporting developers on software engineering tasks (AI4SE), especially bug fixing and management. Particular, I’m trying to explore the following research questions:
(1) How reliable and depandable AI4SE tools?
(2) How can we improve their reliability and trustworthiness?
(3) How can we improve developers’ trust on these tools?
If they are look interesting for you, let's see more about my publications.
Research interests:
[Oct 2023] I have been awarded Google PhD Fellowships in Programming Technology and Software Engineering. Huge thanks to my advisors, colleagues, and collaborators!
Authors:Thanh Le-Cong, Hong Jin Kang, Truong Giang Nguyen, Stefanus Agus Haryono, David Lo, Bach Le, and Thang Huynh Quyet
Venue: ACM 30th Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) 2022, Research Track [Acceptance Rate: 22%]
One-line Abstract: Pruning false positives in static call graph via code features learned by Large Language Model and syntactic features extracted from the original call graph.
Links:
[ICSE'23] Chronos: Time-Aware Zero-Shot Identification of Libraries from Vulnerability Reports
Authors: Yunbo Lyu+, Thanh Le-Cong+, Hong Jin Kang, Ratnadira Widyasari, Zhao Zhipeng, Bach Le, Ming Li, and David Lo
Venue: IEEE/ACM 45th International Conference on Software Engineering (ICSE) 2023, Technical Track [Acceptance Rate: 26%]
One-line Abstract: Identifying vulnerable libraries from vulnerability reports via zero-shot learning and domain-specific mechanisms.
Links:
[TOSEM'24] Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues?
Authors: Yue Liu, Thanh Le-Cong, Ratnadira Widyasari, Chakkrit Tantithamthavorn, Li Li, Bach Le, David Lo
Venue: ACM Transactions on Software Engineering and Methodology
One-line Abstract: An empirical study on code quality issues in ChatGPT-generated code.
Links:
[TSE'23] MiDas: Multi-Granularity Detector for Vulnerability Fixes
Authors: 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, and David Lo
Venue: IEEE Transactions on Software Engineering
One-line Abstract: Identifying vulnerability fixes by analyzing multi-granularity of code changes.
Integrated to internal service of industry partners for managing vulnerability
Links:
[Arxiv] Inferring Properties of Graph Neural Networks
Authors: Dat Nguyen , Hieu M. Vu , Thanh Le-Cong, Bach Le, David Lo, Corina Pasareanu
Venue: Under Review in PLDI 2024
One-line Abstract: The first automatic property inference technique for GNNs using formal verification, graph mining and dynamic analysis
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