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Viewing Publication 1 - 46 from 46

2025

Investigating the Role of LLMs Hyperparameter Tuning and Prompt Engineering to Support Domain ModelingVladyslav Bulhakov, Giordano d'Aloisio, Claudio Di Sipio, Antinisca Di Marco, Davide Di Ruscio. euromicro 2026: 349-366 [doi]

Leveraging synthetic trace generation of modeling operations for intelligent modeling assistants using large language modelsVittoriano Muttillo, Claudio Di Sipio, Riccardo Rubei, Luca Berardinelli. INFSOF, 186:107806, 2025. [doi]

Generate with CodeXHug: A Dataset to Enhance Model Cards with Code Usage PatternsStefano Palombo, Claudio Di Sipio, Juri Di Rocco, Davide Di Ruscio. euromicro 2026: 327-344 [doi]

Automated Recommender System Integration in Model-Based EcosystemsRickson Simioni Pereira, Claudio Di Sipio, Martina de Sanctis, Ludovico Iovino. caise 2025: 20-38 [doi]

DeepMig: A transformer-based approach to support coupled library and code migrationsJuri Di Rocco, Phuong T. Nguyen 0001, Claudio Di Sipio, Riccardo Rubei, Davide Di Ruscio, Massimiliano Di Penta. INFSOF, 177:107588, 2025. [doi]

On the use of large language models in model-driven engineeringJuri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong T. Nguyen 0001, Riccardo Rubei. SoSyM, 24(3):923-948, June 2025. [doi]

Prompt engineering and its implications on the energy consumption of Large Language ModelsRiccardo Rubei, Aicha Moussaid, Claudio Di Sipio, Davide Di Ruscio. greens 2025: 60-67 [doi]

On the Need for Reproducibility Guidelines for Open-Source Games: A itch.io Case StudyClaudio Di Sipio, Andrea D'Angelo, Riccardo Rubei, Cristiano Politowski. cig 2025: 1-8 [doi]

2024

Automatic Categorization of GitHub Actions with Transformers and Few-shot LearningPhuong T. Nguyen 0001, Juri Di Rocco, Claudio Di Sipio, Mudita Shakya, Davide Di Ruscio, Massimiliano Di Penta. esem 2024: 468-474 [doi]

GPTSniffer: A CodeBERT-based classifier to detect source code written by ChatGPTPhuong T. Nguyen 0001, Juri Di Rocco, Claudio Di Sipio, Riccardo Rubei, Davide Di Ruscio, Massimiliano Di Penta. jss, 214:112059, 2024. [doi]

Towards Automating Model-Based Systems Engineering in Industry - An Experience ReportJohan Cederbladh, Luca Berardinelli, Hugo Bruneliere, Antonio Cicchetti, MohammadHadi Dehghani, Claudio Di Sipio, James William Pontes Miranda, Abbas Rahimi, Riccardo Rubei, Jagadish Suryadevara. syscon 2024: 1-8 [doi]

PlayMyData: a curated dataset of multi-platform video gamesAndrea D'Angelo, Claudio Di Sipio, Cristiano Politowski, Riccardo Rubei. msr 2024: 525-529 [doi]

Towards Synthetic Trace Generation of Modeling Operations using In-Context Learning ApproachVittoriano Muttillo, Claudio Di Sipio, Riccardo Rubei, Luca Berardinelli, MohammadHadi Dehghani. ASE 2024: 619-630 [doi]

FRINGE: context-aware FaiRness engineerING in complex software systEmsFabio 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, Giordano d'Aloisio, Antinisca Di Marco. esem 2024: 608-612 [doi]

On the Need for Configurable Travel Recommender Systems: A Systematic Mapping StudyRickson Simioni Pereira, Claudio Di Sipio, Martina de Sanctis, Ludovico Iovino. euromicro 2024: 56-63 [doi]

Automated categorization of pre-trained models in software engineering: A case study with a Hugging Face datasetClaudio Di Sipio, Riccardo Rubei, Juri Di Rocco, Davide Di Ruscio, Phuong T. Nguyen 0001. EASE 2024: 351-356 [doi]

On the use of LLMs to support the development of domain-specific modeling languagesClaudio Di Sipio, Riccardo Rubei, Juri Di Rocco, Davide Di Ruscio, Ludovico Iovino. MoDELS 2024: 596-601 [doi]

LEV4REC: A feature-based approach to engineering RSSEsClaudio Di Sipio, Juri Di Rocco, Davide Di Ruscio, Phuong T. Nguyen 0001. JCL (JVLC), 78:101256, March 2024. [doi]

CodeLL: A Lifelong Learning Dataset to Support the Co-Evolution of Data and Language Models of CodeMartin Weyssow, Claudio Di Sipio, Davide Di Ruscio, Houari A. Sahraoui. msr 2024: 637-641 [doi]

2023

Dealing with Popularity Bias in Recommender Systems for Third-party Libraries: How far Are We?Phuong T. Nguyen 0001, Riccardo Rubei, Juri Di Rocco, Claudio Di Sipio, Davide Di Ruscio, Massimiliano Di Penta. msr 2023: 12-24 [doi]

Supporting Early-Safety Analysis of IoT Systems by Exploiting Testing TechniquesDiego Clerissi, Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Felicien Ihirwe, Leonardo Mariani, Daniela Micucci, Maria Teresa Rossi, Riccardo Rubei. MoDELS 2023: 520-529 [doi]

Fitting missing API puzzles with machine translation techniquesPhuong T. Nguyen, Claudio Di Sipio, Juri Di Rocco, Davide Di Ruscio, Massimiliano Di Penta. eswa, 216:119477, April 2023. [doi]

ResyDuo: Combining Data Models and CF-Based Recommender Systems to Develop Arduino ProjectsJuri Di Rocco, Claudio Di Sipio. MoDELS 2023: 539-548 [doi]

MemoRec: a recommender system for assisting modelers in specifying metamodelsJuri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong T. Nguyen, Alfonso Pierantonio. SoSyM, 22(1):203-223, February 2023. [doi]

HybridRec: A recommender system for tagging GitHub repositoriesJuri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong T. Nguyen 0001, Riccardo Rubei. apin, 53(8):9708-9730, April 2023. [doi]

GitRanking: A ranking of GitHub topics for software classification using active samplingCezar Sas, Andrea Capiluppi, Claudio Di Sipio, Juri Di Rocco, Davide Di Ruscio. SPE, 53(10):1982-2006, October 2023. [doi]

MORGAN: a modeling recommender system based on graph kernelClaudio Di Sipio, Juri Di Rocco, Davide Di Ruscio, Phuong T. Nguyen 0001. SoSyM, 22(5):1427-1449, October 2023. [doi]

2022

DeepLib: Machine translation techniques to recommend upgrades for third-party librariesPhuong T. Nguyen, Juri Di Rocco, Riccardo Rubei, Claudio Di Sipio, Davide Di Ruscio. eswa, 202:117267, 2022. [doi]

Recommending API Function Calls and Code Snippets to Support Software DevelopmentPhuong T. Nguyen, Juri Di Rocco, Claudio Di Sipio, Davide Di Ruscio, Massimiliano Di Penta. TSE, 48(7):2417-2438, 2022. [doi]

Finding with NEMO: a recommender system to forecast the next modeling operationsJuri Di Rocco, Claudio Di Sipio, Phuong T. Nguyen, Davide Di Ruscio, Alfonso Pierantonio. MoDELS 2022: 154-164 [doi]

Endowing third-party libraries recommender systems with explicit user feedback mechanismsRiccardo Rubei, Claudio Di Sipio, Juri Di Rocco, Davide Di Ruscio, Phuong T. Nguyen. WCRE 2022: 817-821 [doi]

Providing upgrade plans for third-party libraries: a recommender system using migration graphsRiccardo Rubei, Davide Di Ruscio, Claudio Di Sipio, Juri Di Rocco, Phuong T. Nguyen. apin, 52(10):12000-12015, 2022. [doi]

Automating the design of recommender systems: from foundational aspects to actual developmentClaudio Di Sipio. MoDELS 2022: 233-236 [doi]

2021

Adversarial Machine Learning: On the Resilience of Third-party Library Recommender SystemsPhuong T. Nguyen, Davide Di Ruscio, Juri Di Rocco, Claudio Di Sipio, Massimiliano Di Penta. EASE 2021: 247-253 [doi]

Adversarial Attacks to API Recommender Systems: Time to Wake Up and Smell the CoffeeƒPhuong T. Nguyen, Claudio Di Sipio, Juri Di Rocco, Massimiliano Di Penta, Davide Di Ruscio. ASE 2021: 253-265 [doi]

Recommending Third-party Library Updates with LSTM Neural NetworksPhuong T. Nguyen, Juri Di Rocco, Riccardo Rubei, Claudio Di Sipio, Davide Di Ruscio. iir 2021: [doi]

A GNN-based Recommender System to Assist the Specification of Metamodels and ModelsJuri Di Rocco, Claudio Di Sipio, Davide Di Ruscio, Phuong Thanh Nguyen. MoDELS 2021: 70-81 [doi]

On the Need for a Body of Knowledge on Recommender Systems (Short paper)Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong T. Nguyen, Claudio Pomo. recsys 2021: [doi]

Development of recommendation systems for software engineering: the CROSSMINER experienceJuri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong T. Nguyen, Riccardo Rubei. ese, 26(4):69, 2021. [doi]

AURYGA: A Recommender System for Game TaggingRiccardo Rubei, Claudio Di Sipio. iir 2021: [doi]

A Low-Code Tool Supporting the Development of Recommender SystemsClaudio Di Sipio, Juri Di Rocco, Davide Di Ruscio, Phuong Thanh Nguyen. recsys 2021: 741-744 [doi]

2020

Automated fruit recognition using EfficientNet and MixNetLinh T. Duong, Phuong T. Nguyen, Claudio Di Sipio, Davide Di Ruscio. cea, 171:105326, 2020. [doi]

TopFilter: An Approach to Recommend Relevant GitHub TopicsJuri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong T. Nguyen, Riccardo Rubei. esem 2020: [doi]

PostFinder: Mining Stack Overflow posts to support software developersRiccardo Rubei, Claudio Di Sipio, Phuong T. Nguyen, Juri Di Rocco, Davide Di Ruscio. INFSOF, 127:106367, 2020. [doi]

Democratizing the development of recommender systems by means of low-code platformsClaudio Di Sipio, Davide Di Ruscio, Phuong T. Nguyen. MoDELS 2020: [doi]

A Multinomial Naïve Bayesian (MNB) Network to Automatically Recommend Topics for GitHub RepositoriesClaudio Di Sipio, Riccardo Rubei, Davide Di Ruscio, Phuong T. Nguyen. EASE 2020: 71-80 [doi]

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