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2020 – today
- 2025
[j17]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)- [j16]Vittoriano Muttillo, Claudio Di Sipio, Riccardo Rubei, Luca Berardinelli:
Leveraging synthetic trace generation of modeling operations for intelligent modeling assistants using large language models. Inf. Softw. Technol. 186: 107806 (2025) - [j15]Giordano d'Aloisio, Claudio Di Sipio, Antinisca Di Marco, Davide Di Ruscio:
Towards early detection of algorithmic bias from dataset's bias symptoms: An empirical study. Inf. Softw. Technol. 188: 107905 (2025) - [j14]Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong T. Nguyen, Riccardo Rubei:
On the use of large language models in model-driven engineering. Softw. Syst. Model. 24(3): 923-948 (2025) - [c30]Rickson Simioni Pereira, Claudio Di Sipio, Martina De Sanctis, Ludovico Iovino:
Automated Recommender System Integration in Model-Based Ecosystems. CAiSE (2) 2025: 20-38 - [c29]Claudio Di Sipio, Andrea D'Angelo, Riccardo Rubei, Cristiano Politowski:
On the Need for Reproducibility Guidelines for Open-Source Games: A itch.io Case Study. CoG 2025: 1-8 - [c28]Stefano Palombo, Claudio Di Sipio, Juri Di Rocco, Davide Di Ruscio:
Generate with CodeXHug: A Dataset to Enhance Model Cards with Code Usage Patterns. SEAA (3) 2025: 327-344 - [c27]Vladyslav Bulhakov, Giordano d'Aloisio, Claudio Di Sipio, Antinisca Di Marco, Davide Di Ruscio:
Investigating the Role of LLMs Hyperparameter Tuning and Prompt Engineering to Support Domain Modeling. SEAA 2025: 349-366 - [c26]Riccardo Rubei, Aicha Moussaid, Claudio Di Sipio, Davide Di Ruscio:
Prompt engineering and its implications on the energy consumption of Large Language Models. GREENS@ICSE 2025: 60-67 - [i22]Riccardo Rubei, Aicha Moussaid, Claudio Di Sipio, Davide Di Ruscio:
Prompt engineering and its implications on the energy consumption of Large Language Models. CoRR abs/2501.05899 (2025) - [i21]Claudio Di Sipio, Juri Di Rocco, Davide Di Ruscio, Vladyslav Bulhakov:
Addressing Popularity Bias in Third-Party Library Recommendations Using LLMs. CoRR abs/2501.10313 (2025) - [i20]Motunrayo Ibiyo, Thinakone Louangdy, Phuong T. Nguyen, Claudio Di Sipio, Davide Di Ruscio:
Detecting Malicious Source Code in PyPI Packages with LLMs: Does RAG Come in Handy? CoRR abs/2504.13769 (2025) - [i19]Lorenzo De Tomasi, Claudio Di Sipio, Antinisca Di Marco, Phuong T. Nguyen:
Simplicity by Obfuscation: Evaluating LLM-Driven Code Transformation with Semantic Elasticity. CoRR abs/2504.14024 (2025) - [i18]Vladyslav Bulhakov, Giordano d'Aloisio, Claudio Di Sipio, Antinisca Di Marco, Davide Di Ruscio:
Investigating the Role of LLMs Hyperparameter Tuning and Prompt Engineering to Support Domain Modeling. CoRR abs/2507.14735 (2025) - 2024
- [j13]Phuong T. Nguyen, Juri Di Rocco, Claudio Di Sipio, Riccardo Rubei, Davide Di Ruscio, Massimiliano Di Penta:
GPTSniffer: A CodeBERT-based classifier to detect source code written by ChatGPT. J. Syst. Softw. 214: 112059 (2024) - [j12]Claudio Di Sipio, Juri Di Rocco, Davide Di Ruscio, Phuong T. Nguyen:
LEV4REC: A feature-based approach to engineering RSSEs. J. Comput. Lang. 78: 101256 (2024) - [c25]Claudio Di Sipio, Riccardo Rubei, Juri Di Rocco, Davide Di Ruscio, Phuong T. Nguyen:
Automated categorization of pre-trained models in software engineering: A case study with a Hugging Face dataset. EASE 2024: 351-356 - [c24]Phuong T. Nguyen, Juri Di Rocco, Claudio Di Sipio, Mudita Shakya, Davide Di Ruscio, Massimiliano Di Penta:
Automatic Categorization of GitHub Actions with Transformers and Few-shot Learning. ESEM 2024: 468-474 - [c23]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, Giordano d'Aloisio, Antinisca Di Marco:
FRINGE: context-aware FaiRness engineerING in complex software systEms. ESEM 2024: 608-612 - [c22]Rickson Simioni Pereira, Claudio Di Sipio, Martina De Sanctis, Ludovico Iovino:
On the Need for Configurable Travel Recommender Systems: A Systematic Mapping Study. SEAA 2024: 56-63 - [c21]Vittoriano Muttillo, Claudio Di Sipio, Riccardo Rubei, Luca Berardinelli, MohammadHadi Dehghani:
Towards Synthetic Trace Generation of Modeling Operations using In-Context Learning Approach. ASE 2024: 619-630 - [c20]Claudio Di Sipio, Riccardo Rubei, Juri Di Rocco, Davide Di Ruscio, Ludovico Iovino:
On the use of LLMs to support the development of domain-specific modeling languages. MoDELS (Companion) 2024: 596-601 - [c19]Andrea D'Angelo, Claudio Di Sipio, Cristiano Politowski, Riccardo Rubei:
PlayMyData: a curated dataset of multi-platform video games. MSR 2024: 525-529 - [c18]Martin Weyssow, Claudio Di Sipio, Davide Di Ruscio, Houari A. Sahraoui:
CodeLL: A Lifelong Learning Dataset to Support the Co-Evolution of Data and Language Models of Code. MSR 2024: 637-641 - [c17]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 - [d4]Claudio Di Sipio, Juri Di Rocco, Davide Di Ruscio, Stefano Palombo:
CofeXHug: A curated dataset of HuggingFace pre-trained models exploited in the GitHub ecosystem. Zenodo, 2024
- [i17]Andrea D'Angelo, Claudio Di Sipio, Cristiano Politowski, Riccardo Rubei:
PlayMyData: a curated dataset of multi-platform video games. CoRR abs/2401.08561 (2024) - [i16]Giordano d'Aloisio, Claudio Di Sipio, Antinisca Di Marco, Davide Di Ruscio:
How fair are we? From conceptualization to automated assessment of fairness definitions. CoRR abs/2404.09919 (2024) - [i15]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) - [i14]Rickson Simioni Pereira, Claudio Di Sipio, Martina De Sanctis, Ludovico Iovino:
On the Need for Configurable Travel Recommender Systems: A Systematic Mapping Study. CoRR abs/2407.11575 (2024) - [i13]Phuong T. Nguyen, Juri Di Rocco, Claudio Di Sipio, Mudita Shakya, Davide Di Ruscio, Massimiliano Di Penta:
Automatic Categorization of GitHub Actions with Transformers and Few-shot Learning. CoRR abs/2407.16946 (2024) - [i12]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) - [i11]Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong T. Nguyen, Riccardo Rubei:
On the use of Large Language Models in Model-Driven Engineering. CoRR abs/2410.17370 (2024) - 2023
- [j11]Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong T. Nguyen, Riccardo Rubei:
HybridRec: A recommender system for tagging GitHub repositories. Appl. Intell. 53(8): 9708-9730 (2023) - [j10]Phuong T. Nguyen, Claudio Di Sipio, Juri Di Rocco, Davide Di Ruscio, Massimiliano Di Penta:
Fitting missing API puzzles with machine translation techniques. Expert Syst. Appl. 216: 119477 (2023) - [j9]Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong T. Nguyen, Alfonso Pierantonio:
MemoRec: a recommender system for assisting modelers in specifying metamodels. Softw. Syst. Model. 22(1): 203-223 (2023) - [j8]Claudio Di Sipio, Juri Di Rocco, Davide Di Ruscio, Phuong T. Nguyen:
MORGAN: a modeling recommender system based on graph kernel. Softw. Syst. Model. 22(5): 1427-1449 (2023) - [j7]Cezar Sas, Andrea Capiluppi, Claudio Di Sipio, Juri Di Rocco, Davide Di Ruscio:
GitRanking: A ranking of GitHub topics for software classification using active sampling. Softw. Pract. Exp. 53(10): 1982-2006 (2023) - [c16]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 - [c15]Juri Di Rocco, Claudio Di Sipio:
ResyDuo: Combining Data Models and CF-Based Recommender Systems to Develop Arduino Projects. MoDELS (Companion) 2023: 539-548 - [c14]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? MSR 2023: 12-24 - [d3]Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong Thanh Nguyen, Riccardo Rubei:
GItome: a curated dataset for README summarization. Version 1. Zenodo, 2023 [all versions] - [d2]Claudio Di Sipio, Juri Di Rocco, Riccardo Rubei, Phuong Thanh Nguyen, Davide Di Ruscio:
Gitome: A curated dataset for GitHub README-related tasks. Version 2. Zenodo, 2023 [all versions] - [i10]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) - [i9]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) - [i8]Juri Di Rocco, Claudio Di Sipio:
ResyDuo: Combining data models and CF-based recommender systems to develop Arduino projects. CoRR abs/2308.13808 (2023) - [i7]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. CoRR abs/2309.02985 (2023) - [i6]Martin Weyssow, Claudio Di Sipio, Davide Di Ruscio, Houari A. Sahraoui:
CodeLL: A Lifelong Learning Dataset to Support the Co-Evolution of Data and Language Models of Code. CoRR abs/2312.12492 (2023) - 2022
- [j6]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. Appl. Intell. 52(10): 12000-12015 (2022) - [j5]Phuong T. Nguyen, Juri Di Rocco, Riccardo Rubei, Claudio Di Sipio, Davide Di Ruscio:
DeepLib: Machine translation techniques to recommend upgrades for third-party libraries. Expert Syst. Appl. 202: 117267 (2022) - [j4]Phuong T. Nguyen, Juri Di Rocco, Claudio Di Sipio, Davide Di Ruscio, Massimiliano Di Penta:
Recommending API Function Calls and Code Snippets to Support Software Development. IEEE Trans. Software Eng. 48(7): 2417-2438 (2022) - [c13]Juri Di Rocco, Claudio Di Sipio, Phuong T. Nguyen, Davide Di Ruscio, Alfonso Pierantonio:
Finding with NEMO: a recommender system to forecast the next modeling operations. MoDELS 2022: 154-164 - [c12]Claudio Di Sipio:
Automating the design of recommender systems: from foundational aspects to actual development. MoDELS (Companion) 2022: 233-236 - [c11]Riccardo Rubei, Claudio Di Sipio, Juri Di Rocco, Davide Di Ruscio, Phuong T. Nguyen:
Endowing third-party libraries recommender systems with explicit user feedback mechanisms. SANER 2022: 817-821 - [i5]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) - [i4]Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong T. Nguyen, Alfonso Pierantonio:
MemoRec: A Recommender System for Assisting Modelers in Specifying Metamodels. CoRR abs/2203.06068 (2022) - [i3]Cezar Sas, Andrea Capiluppi, Claudio Di Sipio, Juri Di Rocco, Davide Di Ruscio:
GitRanking: A Ranking of GitHub Topics for Software Classification using Active Sampling. CoRR abs/2205.09379 (2022) - 2021
- [j3]Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong Thanh Nguyen, Riccardo Rubei:
Development of recommendation systems for software engineering: the CROSSMINER experience. Empir. Softw. Eng. 26(4): 69 (2021) - [c10]Phuong Thanh Nguyen, Davide Di Ruscio, Juri Di Rocco, Claudio Di Sipio, Massimiliano Di Penta:
Adversarial Machine Learning: On the Resilience of Third-party Library Recommender Systems. EASE 2021: 247-253 - [c9]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 - [c8]Riccardo Rubei, Claudio Di Sipio:
AURYGA: A Recommender System for Game Tagging. IIR 2021 - [c7]Phuong T. Nguyen, Claudio Di Sipio, Juri Di Rocco, Massimiliano Di Penta, Davide Di Ruscio:
Adversarial Attacks to API Recommender Systems: Time to Wake Up and Smell the Coffeeƒ. ASE 2021: 253-265 - [c6]Juri Di Rocco, Claudio Di Sipio, Davide Di Ruscio, Phuong Thanh Nguyen:
A GNN-based Recommender System to Assist the Specification of Metamodels and Models. MoDELS 2021: 70-81 - [c5]Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong Thanh Nguyen, Claudio Pomo:
On the Need for a Body of Knowledge on Recommender Systems (Short paper). KaRS/ComplexRec@RecSys 2021 - [c4]Claudio Di Sipio, Juri Di Rocco, Davide Di Ruscio, Phuong Thanh Nguyen:
A Low-Code Tool Supporting the Development of Recommender Systems. RecSys 2021: 741-744 - [d1]Phuong T. Nguyen, Juri Di Rocco, Claudio Di Sipio, Davide Di Ruscio, Massimiliano Di Penta:
crossminer/FOCUS: TSE Focus Replication package. Zenodo, 2021 - [i2]Phuong Thanh Nguyen, Juri Di Rocco, Claudio Di Sipio, Davide Di Ruscio, Massimiliano Di Penta:
Recommending API Function Calls and Code Snippets to Support Software Development. CoRR abs/2102.07508 (2021) - [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]Linh T. Duong, Phuong Thanh Nguyen, Claudio Di Sipio, Davide Di Ruscio:
Automated fruit recognition using EfficientNet and MixNet. Comput. Electron. Agric. 171: 105326 (2020) - [j1]Riccardo Rubei, Claudio Di Sipio, Phuong Thanh Nguyen, Juri Di Rocco, Davide Di Ruscio:
PostFinder: Mining Stack Overflow posts to support software developers. Inf. Softw. Technol. 127: 106367 (2020) - [c3]Claudio Di Sipio, Riccardo Rubei, Davide Di Ruscio, Phuong Thanh Nguyen:
A Multinomial Naïve Bayesian (MNB) Network to Automatically Recommend Topics for GitHub Repositories. EASE 2020: 71-80 - [c2]Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong Thanh Nguyen, Riccardo Rubei:
TopFilter: An Approach to Recommend Relevant GitHub Topics. ESEM 2020: 21:1-21:11 - [c1]Claudio Di Sipio, Davide Di Ruscio, Phuong Thanh Nguyen:
Democratizing the development of recommender systems by means of low-code platforms. MoDELS (Companion) 2020: 68:1-68:9
Coauthor Index
[j17] [j15] [j14] [c28] [c27] [c26] [i22] [i21] [i20] [i18] [j13] [j12] [c25] [c24] [c23] [c20] [c18] [d4] [i16] [i15] [i13] [i11] [j11] [j10] [j9] [j8] [j7] [c16] [c14] [d3] [d2] [i10] [i9] [i7] [i6] [j6] [j5] [j4] [c13] [c11] [i5] [i4] [i3] [j3] [c10] [c9] [c7] [c6] [c5] [c4] [d1] [i2] [i1] [j2] [j1] [c3] [c2] [c1]
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