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Riccardo Rubei
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2020 – today
- 2025
- [j8]Juri Di Rocco, Phuong T. Nguyen, Claudio Di Sipio, Riccardo Rubei, Davide Di Ruscio, Massimiliano Di Penta:
DeepMig: A transformer-based approach to support coupled library and code migrations. Inf. Softw. Technol. 177: 107588 (2025) - 2024
- [j7]Phuong T. Nguyen
, Juri Di Rocco
GPTSniffer: A CodeBERT-based classifier to detect source code written by ChatGPT. J. Syst. Softw. 214: 112059 (2024) - [c15]Muhammad Imran
An Empirical Study on Code Coverage of Performance Testing. EASE 2024: 48-57 - [c14]Claudio Di Sipio
Automated categorization of pre-trained models in software engineering: A case study with a Hugging Face dataset. EASE 2024: 351-356 - [c13]Claudio Di Sipio
On the use of LLMs to support the development of domain-specific modeling languages. MoDELS (Companion) 2024: 596-601 - [c12]Andrea D'Angelo
PlayMyData: a curated dataset of multi-platform video games. MSR 2024: 525-529 - [c11]Johan Cederbladh, Luca Berardinelli, Hugo Bruneliere, Antonio Cicchetti, MohammadHadi Dehghani, Claudio Di Sipio, James William Pontes Miranda, Abbas Rahimi, Riccardo Rubei, Jagadish Suryadevara:
Towards Automating Model-Based Systems Engineering in Industry - An Experience Report. SysCon 2024: 1-8 - [e1]Hessa Alfraihi, Francesco Basciani, Georgiana Caltais, Nicolas Ferry, José Antonio Hernández López, Ludovico Iovino, Robbert Jongeling, Stefan Klikovits, Shekoufeh Kolahdouz Rahimi, Riccardo Rubei, Sobhan Yassipour Tehrani, Javier Troya, Mairieli Wessel, Vadim Zaytsev:
Proceedings of the STAF 2024 Workshops: AgileMDE 2024, LLM4MDE 2024, and MeSS 2024 co-located with the International Conference on Software Technologies: Applications and Foundations (STAF 2024) Enschede, The Netherlands, July 8-11, 2024. CEUR Workshop Proceedings 3727, CEUR-WS.org 2024 [contents] - [i8]Andrea D'Angelo, Claudio Di Sipio, Cristiano Politowski, Riccardo Rubei:
PlayMyData: a curated dataset of multi-platform video games. CoRR abs/2401.08561 (2024) - [i7]Claudio Di Sipio, Riccardo Rubei, Juri Di Rocco, Davide Di Ruscio, Phuong T. Nguyen:
Automated categorization of pre-trained models for software engineering: A case study with a Hugging Face dataset. CoRR abs/2405.13185 (2024) - [i6]Vittoriano Muttillo, Claudio Di Sipio, Riccardo Rubei, Luca Berardinelli, MohammadHadi Dehghani:
Towards Synthetic Trace Generation of Modeling Operations using In-Context Learning Approach. CoRR abs/2408.14259 (2024) - 2023
- [j6]Juri Di Rocco
HybridRec: A recommender system for tagging GitHub repositories. Appl. Intell. 53(8): 9708-9730 (2023) - [c10]Diego Clerissi, Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Felicien Ihirwe, Leonardo Mariani, Daniela Micucci, Maria Teresa Rossi, Riccardo Rubei:
Supporting Early-Safety Analysis of IoT Systems by Exploiting Testing Techniques. MoDELS (Companion) 2023: 520-529 - [c9]Phuong T. Nguyen
Dealing with Popularity Bias in Recommender Systems for Third-party Libraries: How far Are We? MSR 2023: 12-24 - [i5]Phuong T. Nguyen, Riccardo Rubei, Juri Di Rocco, Claudio Di Sipio, Davide Di Ruscio, Massimiliano Di Penta:
Dealing with Popularity Bias in Recommender Systems for Third-party Libraries: How far Are We? CoRR abs/2304.10409 (2023) - [i4]Phuong T. Nguyen, Juri Di Rocco, Claudio Di Sipio, Riccardo Rubei, Davide Di Ruscio, Massimiliano Di Penta:
Is this Snippet Written by ChatGPT? An Empirical Study with a CodeBERT-Based Classifier. CoRR abs/2307.09381 (2023) - [i3]Diego Clerissi, Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Felicien Ihirwe, Leonardo Mariani, Daniela Micucci, Maria Teresa Rossi
Supporting Early-Safety Analysis of IoT Systems by Exploiting Testing Techniques. CoRR abs/2309.02985 (2023) - 2022
- [j5]Riccardo Rubei
Providing upgrade plans for third-party libraries: a recommender system using migration graphs. Appl. Intell. 52(10): 12000-12015 (2022) - [j4]Phuong T. Nguyen
DeepLib: Machine translation techniques to recommend upgrades for third-party libraries. Expert Syst. Appl. 202: 117267 (2022) - [c8]José Antonio Hernández López, Riccardo Rubei, Jesús Sánchez Cuadrado, Davide Di Ruscio
Machine learning methods for model classification: a comparative study. MoDELS 2022: 165-175 - [c7]Riccardo Rubei, Claudio Di Sipio, Juri Di Rocco, Davide Di Ruscio
Endowing third-party libraries recommender systems with explicit user feedback mechanisms. SANER 2022: 817-821 - [i2]Riccardo Rubei, Davide Di Ruscio, Claudio Di Sipio, Juri Di Rocco, Phuong T. Nguyen:
Providing Upgrade Plans for Third-party Libraries: A Recommender System using Migration Graphs. CoRR abs/2201.08201 (2022) - 2021
- [j3]Juri Di Rocco
Development of recommendation systems for software engineering: the CROSSMINER experience. Empir. Softw. Eng. 26(4): 69 (2021) - [c6]Phuong Thanh Nguyen, Juri Di Rocco, Riccardo Rubei, Claudio Di Sipio, Davide Di Ruscio:
Recommending Third-party Library Updates with LSTM Neural Networks. IIR 2021 - [c5]Riccardo Rubei, Claudio Di Sipio:
AURYGA: A Recommender System for Game Tagging. IIR 2021 - [c4]Riccardo Rubei, Juri Di Rocco
A Lightweight Approach for the Automated Classification and Clustering of Metamodels. MoDELS (Companion) 2021: 477-482 - [i1]Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong Thanh Nguyen, Riccardo Rubei:
Development of recommendation systems for software engineering: the CROSSMINER experience. CoRR abs/2103.06987 (2021) - 2020
- [j2]Riccardo Rubei
PostFinder: Mining Stack Overflow posts to support software developers. Inf. Softw. Technol. 127: 106367 (2020) - [j1]Phuong Thanh Nguyen
An automated approach to assess the similarity of GitHub repositories. Softw. Qual. J. 28(2): 595-631 (2020) - [c3]Claudio Di Sipio
A Multinomial Naïve Bayesian (MNB) Network to Automatically Recommend Topics for GitHub Repositories. EASE 2020: 71-80 - [c2]Juri Di Rocco
TopFilter: An Approach to Recommend Relevant GitHub Topics. ESEM 2020: 21:1-21:11
2010 – 2019
- 2018
- [c1]Phuong Thanh Nguyen
CrossSim: Exploiting Mutual Relationships to Detect Similar OSS Projects. SEAA 2018: 388-395
Coauthor Index
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