35 citations · 40 across the 15 of their papers we have counts for
16 papers
Developing LLM-based Multi-Agent Systems in Software Engineering: A Mixed-Method Experience Report
Mariama Celi Serafim De Oliveira, Motunrayo Osatohanmen Ibiyo, Marco Gianrusso +3
The proliferation of Generative Artificial Intelligence (Gen AI) powered by large language models (LLMs) has transformed the software development process, introducing new paradigms…
The Illusion of Agentic Complexity in README.md Generation: Evaluating Single-Agent vs. Multi-Agent RAG Systems
Abu Saleh, Tesfay Welegebreal Tesfay, Phuong T. Nguyen +3
Large Language Models (LLMs) are increasingly utilized to automate several software engineering tasks, including code completion, code summarization, testing, and the generation of…
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…
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…
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…
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…
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…
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…
Automatic Categorization of GitHub Actions with Transformers and Few-shot Learning
Phuong T. Nguyen, Juri Di Rocco, Claudio Di Sipio +3
In the GitHub ecosystem, workflows are used as an effective means to automate development tasks and to set up a Continuous Integration and Delivery (CI/CD pipeline). GitHub Actions…
Good things come in three: Generating SO Post Titles with Pre-Trained Models, Self Improvement and Post Ranking
Duc Anh Le, Anh M. T. Bui, Phuong T. Nguyen +1
Stack Overflow is a prominent Q and A forum, supporting developers in seeking suitable resources on programming-related matters. Having high-quality question titles is an effective…
When simplicity meets effectiveness: Detecting code comments coherence with word embeddings and LSTM
Michael Dubem Igbomezie, Phuong T. Nguyen, Davide Di Ruscio
Code comments play a crucial role in software development, as they provide programmers with practical information, allowing them to understand better the intent and semantics of th…
Automated categorization of pre-trained models for software engineering: A case study with a Hugging Face dataset
Claudio Di Sipio, Riccardo Rubei, Juri Di Rocco +2
Software engineering (SE) activities have been revolutionized by the advent of pre-trained models (PTMs), defined as large machine learning (ML) models that can be fine-tuned to pe…
Is this Snippet Written by ChatGPT? An Empirical Study with a CodeBERT-Based Classifier
Phuong T. Nguyen, Juri Di Rocco, Claudio Di Sipio +3
Since its launch in November 2022, ChatGPT has gained popularity among users, especially programmers who use it as a tool to solve development problems. However, while offering a p…
Dealing with Popularity Bias in Recommender Systems for Third-party Libraries: How far Are We?
Phuong T. Nguyen, Riccardo Rubei, Juri Di Rocco +3
Recommender systems for software engineering (RSSEs) assist software engineers in dealing with a growing information overload when discerning alternative development solutions. Whi…
Development of recommendation systems for software engineering: the CROSSMINER experience
Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio +2
To perform their daily tasks, developers intensively make use of existing resources by consulting open-source software (OSS) repositories. Such platforms contain rich data sources,…
Recommending API Function Calls and Code Snippets to Support Software Development
Phuong T. Nguyen, Juri Di Rocco, Claudio Di Sipio +2
Software development activity has reached a high degree of complexity, guided by the heterogeneity of the components, data sources, and tasks. The proliferation of open-source soft…