activity
20212026
most citedDevelopment of recommendation systems for software engineering: the CROSSMINER experience

35 citations · 36 across the 4 of their papers we have counts for

collaborators

8 papers

cs.SE2026

Automated Summarization of Software Documents: An LLM-based Multi-Agent Approach

Duc S. H. Nguyen, Minh T. Nguyen, Phuong T. Nguyen +2

Large Language Models (LLMs) and LLM-based Multi-Agent Systems (MAS) are revolutionizing software engineering (SE) by advancing automation, decision-making, and knowledge processin…

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…

cs.SE2025

Detecting Malicious Source Code in PyPI Packages with LLMs: Does RAG Come in Handy?

Motunrayo Ibiyo, Thinakone Louangdy, Phuong T. Nguyen +2

Malicious software packages in open-source ecosystems, such as PyPI, pose growing security risks. Unlike traditional vulnerabilities, these packages are intentionally designed to d…

cs.SE2025

Teamwork makes the dream work: LLMs-Based Agents for GitHub README.MD Summarization

Duc S. H. Nguyen, Bach G. Truong, Phuong T. Nguyen +2

The proliferation of Large Language Models (LLMs) in recent years has realized many applications in various domains. Being trained with a huge of amount of data coming from various…

cs.SE2024

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.SE2024

On the use of Large Language Models in Model-Driven Engineering

Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio +2

Model-Driven Engineering (MDE) has seen significant advancements with the integration of Machine Learning (ML) and Deep Learning (DL) techniques. Building upon the groundwork of pr…