6 papers
XREPOTEST: Benchmarking Multilingual Repository-Level Unit Test Generation for Large Language Models
Dung Le Quang, Dong Cao Van, Nam Le Hai +3
Large language models (LLMs) have shown promise for automated unit test generation, but existing evaluations largely rely on standalone settings and a narrow set of programming lan…
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…
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…
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…
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…
ROSE: Transformer-Based Refactoring Recommendation for Architectural Smells
Samal Nursapa, Anastassiya Samuilova, Alessio Bucaioni +1
Architectural smells such as God Class, Cyclic Dependency, and Hub-like Dependency degrade software quality and maintainability. Existing tools detect such smells but rarely sugges…