collaborators

7 papers

cs.SE2026

Which Neurons Detect Malicious Code? A Probing Study of LLM Security Knowledge

Lam D. Dao, Vang T. Nguyen, Anh M. T. Bui +1

Background. Large language models (LLMs) have become increasingly capable of understanding and generating source code, leading to their widespread adoption in software engineering…

cs.SE2026

Towards Knowledge Alignment in Code LLMs: Contrastive Unlearning for Evolving APIs

Huy Q. Tran, Dang H. Vu, Tuyen N. Dinh +4

Large Language Models (LLMs) have recently achieved strong performance in code generation. However, due to knowledge cut-off and the rapid evolution of software libraries, they oft…

cs.SE2025

Larger Is Not Always Better: Leveraging Structured Code Diffs for Comment Inconsistency Detection

Phong Nguyen, Anh M. T. Bui, Phuong T. Nguyen

Ensuring semantic consistency between source code and its accompanying comments is crucial for program comprehension, effective debugging, and long-term maintainability. Comment in…

cs.SE2025

Detection of Technical Debt in Java Source Code

Nam Le Hai, Anh M. T. Bui, Phuong T. Nguyen +2

Technical debt (TD) describes the additional costs that emerge when developers have opted for a quick and easy solution to a problem, rather than a more effective and well-designed…

cs.SE2025

When Retriever Meets Generator: A Joint Model for Code Comment Generation

Tien P. T. Le, Anh M. T. Bui, Huy N. D. Pham +2

Automatically generating concise, informative comments for source code can lighten documentation effort and accelerate program comprehension. Retrieval-augmented approaches first f…

cs.SE2025

Bake Two Cakes with One Oven: RL for Defusing Popularity Bias and Cold-start in Third-Party Library Recommendations

Minh Hoang Vuong, Anh M. T. Bui, Phuong T. Nguyen +1

Third-party libraries (TPLs) have become an integral part of modern software development, enhancing developer productivity and accelerating time-to-market. However, identifying sui…