74 citations · 93 across the 10 of their papers we have counts for
11 papers
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…
Many Hands Make Light Work: An LLM-based Multi-Agent System for Detecting Malicious PyPI Packages
Muhammad Umar Zeshan, Motunrayo Ibiyo, Claudio Di Sipio +2
Malicious code in open-source repositories such as PyPI poses a growing threat to software supply chains. Traditional rule-based tools often overlook the semantic patterns in sourc…
Addressing Popularity Bias in Third-Party Library Recommendations Using LLMs
Claudio Di Sipio, Juri Di Rocco, Davide Di Ruscio +1
Recommender systems for software engineering (RSSE) play a crucial role in automating development tasks by providing relevant suggestions according to the developer's context. Howe…
Prompt engineering and its implications on the energy consumption of Large Language Models
Riccardo Rubei, Aicha Moussaid, Claudio di Sipio +1
Reducing the environmental impact of AI-based software systems has become critical. The intensive use of large language models (LLMs) in software engineering poses severe challenge…
Supporting Early-Safety Analysis of IoT Systems by Exploiting Testing Techniques
Diego Clerissi, Juri Di Rocco, Davide Di Ruscio +6
IoT systems complexity and susceptibility to failures pose significant challenges in ensuring their reliable operation Failures can be internally generated or caused by external fa…
A domain-specific modeling and analysis environment for complex IoT applications
Felicien Ihirwe, Davide Di Ruscio, Silvia Mazzini +1
To cope with the complexities found in the Internet of Things domain, designers and developers of IoT applications demand practical tools. Several model-driven engineering methodol…