A Multinomial Naïve Bayesian (MNB) Network to Automatically Recommend Topics for GitHub Repositories. - Claudio Di Sipio; Riccardo Rubei; Davide Di Ruscio; Phuong Thanh Nguyen 001 (EASE, 2020)

TopFilter: An Approach to Recommend Relevant GitHub Topics. - Juri Di Rocco; Davide Di Ruscio; Claudio Di Sipio; Phuong Thanh Nguyen 001; Riccardo Rubei (ESEM, 2020)

Democratizing the development of recommender systems by means of low-code platforms. - Claudio Di Sipio; Davide Di Ruscio; Phuong Thanh Nguyen 001 (MoDELS (Companion), 2020)

Automated fruit recognition using EfficientNet and MixNet. - Linh T. Duong; Phuong Thanh Nguyen 001; Claudio Di Sipio; Davide Di Ruscio (Comput. Electron. Agric., 2020)

PostFinder: Mining Stack Overflow posts to support software developers. - Riccardo Rubei; Claudio Di Sipio; Phuong Thanh Nguyen 001; Juri Di Rocco; Davide Di Ruscio (Inf. Softw. Technol., 2020)

Adversarial Machine Learning: On the Resilience of Third-party Library Recommender Systems. - Phuong Thanh Nguyen 001; Davide Di Ruscio; Juri Di Rocco; Claudio Di Sipio; Massimiliano Di Penta (EASE, 2021)

Recommending Third-party Library Updates with LSTM Neural Networks. - Phuong Thanh Nguyen 001; Juri Di Rocco; Riccardo Rubei; Claudio Di Sipio; Davide Di Ruscio (IIR, 2021)

AURYGA: A Recommender System for Game Tagging. - Riccardo Rubei; Claudio Di Sipio (IIR, 2021)

Adversarial Attacks to API Recommender Systems: Time to Wake Up and Smell the Coffeeƒ. - Phuong T. Nguyen 001; Claudio Di Sipio; Juri Di Rocco; Massimiliano Di Penta; Davide Di Ruscio (ASE, 2021)

A GNN-based Recommender System to Assist the Specification of Metamodels and Models. - Juri Di Rocco; Claudio Di Sipio; Davide Di Ruscio; Phuong Thanh Nguyen 001 (MoDELS, 2021)

On the Need for a Body of Knowledge on Recommender Systems (Short paper). - Juri Di Rocco; Davide Di Ruscio; Claudio Di Sipio; Phuong Thanh Nguyen 001; Claudio Pomo (KaRS/ComplexRec@RecSys, 2021)

A Low-Code Tool Supporting the Development of Recommender Systems. - Claudio Di Sipio; Juri Di Rocco; Davide Di Ruscio; Phuong Thanh Nguyen 001 (RecSys, 2021)

Development of recommendation systems for software engineering: the CROSSMINER experience. - Juri Di Rocco; Davide Di Ruscio; Claudio Di Sipio; Phuong Thanh Nguyen 001; Riccardo Rubei (Empir. Softw. Eng., 2021)

crossminer/FOCUS: TSE Focus Replication package. - Phuong T. Nguyen 001; Juri Di Rocco; Claudio Di Sipio; Davide Di Ruscio; Massimiliano Di Penta (Zenodo, 2021)

Finding with NEMO: a recommender system to forecast the next modeling operations. - Juri Di Rocco; Claudio Di Sipio; Phuong T. Nguyen 001; Davide Di Ruscio; Alfonso Pierantonio (MoDELS, 2022)

Automating the design of recommender systems: from foundational aspects to actual development. - Claudio Di Sipio (MoDELS (Companion), 2022)

Endowing third-party libraries recommender systems with explicit user feedback mechanisms. - Riccardo Rubei; Claudio Di Sipio; Juri Di Rocco; Davide Di Ruscio; Phuong T. Nguyen 001 (SANER, 2022)

Providing upgrade plans for third-party libraries: a recommender system using migration graphs. - Riccardo Rubei; Davide Di Ruscio; Claudio Di Sipio; Juri Di Rocco; Phuong T. Nguyen 001 (Appl. Intell., 2022)

DeepLib: Machine translation techniques to recommend upgrades for third-party libraries. - Phuong T. Nguyen 001; Juri Di Rocco; Riccardo Rubei; Claudio Di Sipio; Davide Di Ruscio (Expert Syst. Appl., 2022)

Recommending API Function Calls and Code Snippets to Support Software Development. - Phuong T. Nguyen 001; Juri Di Rocco; Claudio Di Sipio; Davide Di Ruscio; Massimiliano Di Penta (IEEE Trans. Software Eng., 2022)

Supporting Early-Safety Analysis of IoT Systems by Exploiting Testing Techniques. - Diego Clerissi; Juri Di Rocco; Davide Di Ruscio; Claudio Di Sipio; Felicien Ihirwe; Leonardo Mariani; Daniela Micucci; Maria Teresa Rossi; Riccardo Rubei (MoDELS (Companion), 2023)

ResyDuo: Combining Data Models and CF-Based Recommender Systems to Develop Arduino Projects. - Juri Di Rocco; Claudio Di Sipio (MoDELS (Companion), 2023)

Dealing with Popularity Bias in Recommender Systems for Third-party Libraries: How far Are We? - Phuong T. Nguyen 001; Riccardo Rubei; Juri Di Rocco; Claudio Di Sipio; Davide Di Ruscio; Massimiliano Di Penta (MSR, 2023)

Is this Snippet Written by ChatGPT? An Empirical Study with a CodeBERT-Based Classifier. - Phuong T. Nguyen 001; Juri Di Rocco; Claudio Di Sipio; Riccardo Rubei; Davide Di Ruscio; Massimiliano Di Penta (CoRR, 2023)

MemoRec: a recommender system for assisting modelers in specifying metamodels. - Juri Di Rocco; Davide Di Ruscio; Claudio Di Sipio; Phuong T. Nguyen 001; Alfonso Pierantonio (Softw. Syst. Model., 2023)

HybridRec: A recommender system for tagging GitHub repositories. - Juri Di Rocco; Davide Di Ruscio; Claudio Di Sipio; Phuong T. Nguyen 001; Riccardo Rubei (Appl. Intell., 2023)

Fitting missing API puzzles with machine translation techniques. - Phuong T. Nguyen 001; Claudio Di Sipio; Juri Di Rocco; Davide Di Ruscio; Massimiliano Di Penta (Expert Syst. Appl., 2023)

MORGAN: a modeling recommender system based on graph kernel. - Claudio Di Sipio; Juri Di Rocco; Davide Di Ruscio; Phuong T. Nguyen 001 (Softw. Syst. Model., 2023)

GitRanking: A ranking of GitHub topics for software classification using active sampling. - Cezar Sas; Andrea Capiluppi; Claudio Di Sipio; Juri Di Rocco; Davide Di Ruscio (Softw. Pract. Exp., 2023)

GItome: a curated dataset for README summarization. - Juri Di Rocco; Davide Di Ruscio; Claudio Di Sipio; Phuong Thanh Nguyen 001; Riccardo Rubei (Zenodo, 2023)

Gitome: A curated dataset for GitHub README-related tasks. - Claudio Di Sipio; Juri Di Rocco; Riccardo Rubei; Phuong Thanh Nguyen 001; Davide Di Ruscio (Zenodo, 2023)

Automated categorization of pre-trained models in software engineering: A case study with a Hugging Face dataset. - Claudio Di Sipio; Riccardo Rubei; Juri Di Rocco; Davide Di Ruscio; Phuong T. Nguyen 001 (EASE, 2024)

Automatic Categorization of GitHub Actions with Transformers and Few-shot Learning. - Phuong T. Nguyen 001; Juri Di Rocco; Claudio Di Sipio; Mudita Shakya; Davide Di Ruscio; Massimiliano Di Penta (ESEM, 2024)

FRINGE: context-aware FaiRness engineerING in complex software systEms. - Fabio Palomba; Andrea Di Sorbo; Davide Di Ruscio; Filomena Ferrucci; Gemma Catolino; Giammaria Giordano; Dario Di Dario; Gianmario Voria; Viviana Pentangelo; Maria Tortorella; Arnaldo Sgueglia; Claudio Di Sipio; et al. (ESEM, 2024)

On the Need for Configurable Travel Recommender Systems: A Systematic Mapping Study. - Rickson Simioni Pereira; Claudio Di Sipio; Martina De Sanctis; Ludovico Iovino (SEAA, 2024)

Towards Synthetic Trace Generation of Modeling Operations using In-Context Learning Approach. - Vittoriano Muttillo; Claudio Di Sipio; Riccardo Rubei; Luca Berardinelli; MohammadHadi Dehghani (ASE, 2024)

On the use of LLMs to support the development of domain-specific modeling languages. - Claudio Di Sipio; Riccardo Rubei; Juri Di Rocco; Davide Di Ruscio; Ludovico Iovino (MoDELS (Companion), 2024)

PlayMyData: a curated dataset of multi-platform video games. - Andrea D'Angelo; Claudio Di Sipio; Cristiano Politowski; Riccardo Rubei (MSR, 2024)

CodeLL: A Lifelong Learning Dataset to Support the Co-Evolution of Data and Language Models of Code. - Martin Weyssow; Claudio Di Sipio; Davide Di Ruscio; Houari A. Sahraoui (MSR, 2024)

Towards Automating Model-Based Systems Engineering in Industry - An Experience Report. - Johan Cederbladh; Luca Berardinelli; Hugo Bruneliere; Antonio Cicchetti; MohammadHadi Dehghani; Claudio Di Sipio; James William Pontes Miranda; Abbas Rahimi; Riccardo Rubei; Jagadish Suryadevara (SysCon, 2024)

How fair are we? From conceptualization to automated assessment of fairness definitions. - Giordano d'Aloisio; Claudio Di Sipio; Antinisca Di Marco; Davide Di Ruscio (CoRR, 2024)

GPTSniffer: A CodeBERT-based classifier to detect source code written by ChatGPT. - Phuong T. Nguyen 001; Juri Di Rocco; Claudio Di Sipio; Riccardo Rubei; Davide Di Ruscio; Massimiliano Di Penta (J. Syst. Softw., 2024)

LEV4REC: A feature-based approach to engineering RSSEs. - Claudio Di Sipio; Juri Di Rocco; Davide Di Ruscio; Phuong T. Nguyen 001 (J. Comput. Lang., 2024)

CofeXHug: A curated dataset of HuggingFace pre-trained models exploited in the GitHub ecosystem. - Claudio Di Sipio; Juri Di Rocco; Davide Di Ruscio; Stefano Palombo (Zenodo, 2024)

Automated Recommender System Integration in Model-Based Ecosystems. - Rickson Simioni Pereira; Claudio Di Sipio; Martina De Sanctis; Ludovico Iovino (CAiSE (2), 2025)

On the Need for Reproducibility Guidelines for Open-Source Games: A itch.io Case Study. - Claudio Di Sipio; Andrea D'Angelo; Riccardo Rubei; Cristiano Politowski (CoG, 2025)

Prompt engineering and its implications on the energy consumption of Large Language Models. - Riccardo Rubei; Aicha Moussaid; Claudio Di Sipio; Davide Di Ruscio (GREENS@ICSE, 2025)

Leveraging synthetic trace generation of modeling operations for intelligent modeling assistants using large language models. - Vittoriano Muttillo; Claudio Di Sipio; Riccardo Rubei; Luca Berardinelli (Inf. Softw. Technol., 2025)

DeepMig: A transformer-based approach to support coupled library and code migrations. - Juri Di Rocco; Phuong T. Nguyen 001; Claudio Di Sipio; Riccardo Rubei; Davide Di Ruscio; Massimiliano Di Penta (Inf. Softw. Technol., 2025)

Addressing Popularity Bias in Third-Party Library Recommendations Using LLMs. - Claudio Di Sipio; Juri Di Rocco; Davide Di Ruscio; Vladyslav Bulhakov (CoRR, 2025)

Detecting Malicious Source Code in PyPI Packages with LLMs: Does RAG Come in Handy? - Motunrayo Ibiyo; Thinakone Louangdy; Phuong T. Nguyen 001; Claudio Di Sipio; Davide Di Ruscio (CoRR, 2025)

Simplicity by Obfuscation: Evaluating LLM-Driven Code Transformation with Semantic Elasticity. - Lorenzo De Tomasi; Claudio Di Sipio; Antinisca Di Marco; Phuong T. Nguyen 001 (CoRR, 2025)

On the use of large language models in model-driven engineering. - Juri Di Rocco; Davide Di Ruscio; Claudio Di Sipio; Phuong T. Nguyen 001; Riccardo Rubei (Softw. Syst. Model., 2025)

Investigating the Role of LLMs Hyperparameter Tuning and Prompt Engineering to Support Domain Modeling. - Vladyslav Bulhakov; Giordano d'Aloisio; Claudio Di Sipio; Antinisca Di Marco; Davide Di Ruscio (CoRR, 2025)