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Claudio Di Sipio
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2020 – today
- 2025
- [j14]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
- [j13]Phuong T. Nguyen
, Juri Di Rocco
GPTSniffer: A CodeBERT-based classifier to detect source code written by ChatGPT. J. Syst. Softw. 214: 112059 (2024) - [j12]Claudio Di Sipio
LEV4REC: A feature-based approach to engineering RSSEs. J. Comput. Lang. 78: 101256 (2024) - [c23]Claudio Di Sipio
Automated categorization of pre-trained models in software engineering: A case study with a Hugging Face dataset. EASE 2024: 351-356 - [c22]Phuong T. Nguyen
Automatic Categorization of GitHub Actions with Transformers and Few-shot Learning. ESEM 2024: 468-474 - [c21]Fabio Palomba
FRINGE: context-aware FaiRness engineerING in complex software systEms. ESEM 2024: 608-612 - [c20]Claudio Di Sipio
On the use of LLMs to support the development of domain-specific modeling languages. MoDELS (Companion) 2024: 596-601 - [c19]Andrea D'Angelo
PlayMyData: a curated dataset of multi-platform video games. MSR 2024: 525-529 - [c18]Martin Weyssow
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 - [i16]Andrea D'Angelo, Claudio Di Sipio, Cristiano Politowski, Riccardo Rubei:
PlayMyData: a curated dataset of multi-platform video games. CoRR abs/2401.08561 (2024) - [i15]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) - [i14]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) - [i13]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) - [i12]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) - [i11]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
- [j11]Juri Di Rocco
HybridRec: A recommender system for tagging GitHub repositories. Appl. Intell. 53(8): 9708-9730 (2023) - [j10]Phuong T. Nguyen
Fitting missing API puzzles with machine translation techniques. Expert Syst. Appl. 216: 119477 (2023) - [j9]Juri Di Rocco
MemoRec: a recommender system for assisting modelers in specifying metamodels. Softw. Syst. Model. 22(1): 203-223 (2023) - [j8]Claudio Di Sipio
MORGAN: a modeling recommender system based on graph kernel. Softw. Syst. Model. 22(5): 1427-1449 (2023) - [j7]Cezar Sas
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
Dealing with Popularity Bias in Recommender Systems for Third-party Libraries: How far Are We? MSR 2023: 12-24 - [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
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
Providing upgrade plans for third-party libraries: a recommender system using migration graphs. Appl. Intell. 52(10): 12000-12015 (2022) - [j5]Phuong T. Nguyen
DeepLib: Machine translation techniques to recommend upgrades for third-party libraries. Expert Syst. Appl. 202: 117267 (2022) - [j4]Phuong T. Nguyen
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
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
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
Development of recommendation systems for software engineering: the CROSSMINER experience. Empir. Softw. Eng. 26(4): 69 (2021) - [c10]Phuong Thanh Nguyen
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
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
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
A Low-Code Tool Supporting the Development of Recommender Systems. RecSys 2021: 741-744 - [d1]Phuong T. Nguyen, Juri Di Rocco
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
Automated fruit recognition using EfficientNet and MixNet. Comput. Electron. Agric. 171: 105326 (2020) - [j1]Riccardo Rubei
PostFinder: Mining Stack Overflow posts to support software developers. Inf. Softw. Technol. 127: 106367 (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 - [c1]Claudio Di Sipio
Democratizing the development of recommender systems by means of low-code platforms. MoDELS (Companion) 2020: 68:1-68:9
Coauthor Index
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last updated on 2024-11-19 20:48 CET by the dblp team
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