Pecorelli, Fabiano
Pecorelli, Fabiano
Dipartimento di Informatica/DI
A critical comparison on six static analysis tools: Detection, agreement, and precision
2023-01-01 Lenarduzzi, Valentina; Pecorelli, Fabiano; Saarimaki, Nyyti; Lujan, Savanna; Palomba, Fabio
A large empirical assessment of the role of data balancing in machine-learning-based code smell detection
2020-01-01 Pecorelli, F.; Di Nucci, D.; De Roover, C.; De Lucia, A.
A Multivocal Literature Review of MLOps Tools and Features
2022-01-01 Recupito, Gilberto; Pecorelli, Fabiano; Catolino, Gemma; Moreschini, Sergio; Nucci, Dario Di; Palomba, Fabio; Tamburri, Damian A.
A preliminary evaluation on the relationship among architectural and test smells
2022-01-01 De Stefano, M.; Pecorelli, F.; Di Nucci, D.; De Lucia, A.
A preliminary study on the adequacy of static analysis warnings with respect to code smell prediction
2020-01-01 Lujan, S.; Pecorelli, F.; Palomba, F.; De Lucia, A.; Lenarduzzi, V.
Acceptance and Development of Quantum Computing in the Netherlands and Germany: Barriers and Remedies From a Multi-Stakeholder Perspective
2024-01-01 Martens, J.; Kumara, I.; Di Nucci, D.; Pecorelli, F.; Monsieur, G.; Tamburri, D. A.; Van Den Heuvel, W. -J.
Adaptive selection of classifiers for bug prediction: A large-scale empirical analysis of its performances and a benchmark study
2021-01-01 Pecorelli, F.; Di Nucci, D.
CASpER: A Plug-in for Automated Code Smell Detection and Refactoring
2020-01-01 De Stefano, M.; Gambardella, M. S.; Pecorelli, F.; Palomba, F.; De Lucia, A.
CATTO: Just-in-time Test Case Selection and Execution
2022-01-01 D'Aragona, Da; Pecorelli, F; Romano, S; Scanniello, G; Baldassarre, Mt; Janes, A; Lenarduzzi, V
Comparing heuristic and machine learning approaches for metric-based code smell detection
2019-01-01 Pecorelli, Fabiano; Palomba, F.; Di Nucci, D.; De Lucia, A.
Comparing within-and cross-project machine learning algorithms for code smell detection
2021-01-01 De Stefano, M.; Pecorelli, F.; Palomba, F.; De Lucia, A.
Developer-Driven Code Smell Prioritization
2020-01-01 Pecorelli, F.; Palomba, F.; Khomh, F.; De Lucia, A.
Just-in-time test smell detection and refactoring: The DARTS project
2020-01-01 Lambiase, S.; Cupito, A.; Pecorelli, F.; De Lucia, A.; Palomba, F.
Machine learning-based test smell detection
2024-01-01 Pontillo, V.; Amoroso d'Aragona, D.; Pecorelli, F.; Di Nucci, D.; Ferrucci, F.; Palomba, F.
On the adequacy of static analysis warnings with respect to code smell prediction
2022-01-01 Pecorelli, F.; Lujan, S.; Lenarduzzi, V.; Palomba, F.; De Lucia, A.
On the role of data balancing for machine learning-based code smell detection
2019-01-01 Pecorelli, F.; Di Nucci, D.; De Roover, C.; De Lucia, A.
Predicting The Energy Consumption Level of Java Classes in Android Apps: An Exploratory Analysis
2022-01-01 Iannone, E.; De Stefano, M.; Pecorelli, F.; De Lucia, A.
Refactoring android-specific energy smells: A plugin for android studio
2020-01-01 Iannone, E.; Pecorelli, F.; Di Nucci, D.; Palomba, F.; De Lucia, A.
Refactoring Recommendations Based on the Optimization of Socio-Technical Congruence
2020-01-01 De Stefano, M.; Pecorelli, F.; Tamburri, D. A.; Palomba, F.; De Lucia, A
Software engineering for quantum programming: How far are we?
2022-01-01 De Stefano, M.; Pecorelli, F.; Di Nucci, D.; Palomba, F.; De Lucia, A.
| Titolo | Data di pubblicazione | Autore(i) | File |
|---|---|---|---|
| A critical comparison on six static analysis tools: Detection, agreement, and precision | 1-gen-2023 | Lenarduzzi, Valentina; Pecorelli, Fabiano; Saarimaki, Nyyti; Lujan, Savanna; Palomba, Fabio | |
| A large empirical assessment of the role of data balancing in machine-learning-based code smell detection | 1-gen-2020 | Pecorelli, F.; Di Nucci, D.; De Roover, C.; De Lucia, A. | |
| A Multivocal Literature Review of MLOps Tools and Features | 1-gen-2022 | Recupito, Gilberto; Pecorelli, Fabiano; Catolino, Gemma; Moreschini, Sergio; Nucci, Dario Di; Palomba, Fabio; Tamburri, Damian A. | |
| A preliminary evaluation on the relationship among architectural and test smells | 1-gen-2022 | De Stefano, M.; Pecorelli, F.; Di Nucci, D.; De Lucia, A. | |
| A preliminary study on the adequacy of static analysis warnings with respect to code smell prediction | 1-gen-2020 | Lujan, S.; Pecorelli, F.; Palomba, F.; De Lucia, A.; Lenarduzzi, V. | |
| Acceptance and Development of Quantum Computing in the Netherlands and Germany: Barriers and Remedies From a Multi-Stakeholder Perspective | 1-gen-2024 | Martens, J.; Kumara, I.; Di Nucci, D.; Pecorelli, F.; Monsieur, G.; Tamburri, D. A.; Van Den Heuvel, W. -J. | |
| Adaptive selection of classifiers for bug prediction: A large-scale empirical analysis of its performances and a benchmark study | 1-gen-2021 | Pecorelli, F.; Di Nucci, D. | |
| CASpER: A Plug-in for Automated Code Smell Detection and Refactoring | 1-gen-2020 | De Stefano, M.; Gambardella, M. S.; Pecorelli, F.; Palomba, F.; De Lucia, A. | |
| CATTO: Just-in-time Test Case Selection and Execution | 1-gen-2022 | D'Aragona, Da; Pecorelli, F; Romano, S; Scanniello, G; Baldassarre, Mt; Janes, A; Lenarduzzi, V | |
| Comparing heuristic and machine learning approaches for metric-based code smell detection | 1-gen-2019 | Pecorelli, Fabiano; Palomba, F.; Di Nucci, D.; De Lucia, A. | |
| Comparing within-and cross-project machine learning algorithms for code smell detection | 1-gen-2021 | De Stefano, M.; Pecorelli, F.; Palomba, F.; De Lucia, A. | |
| Developer-Driven Code Smell Prioritization | 1-gen-2020 | Pecorelli, F.; Palomba, F.; Khomh, F.; De Lucia, A. | |
| Just-in-time test smell detection and refactoring: The DARTS project | 1-gen-2020 | Lambiase, S.; Cupito, A.; Pecorelli, F.; De Lucia, A.; Palomba, F. | |
| Machine learning-based test smell detection | 1-gen-2024 | Pontillo, V.; Amoroso d'Aragona, D.; Pecorelli, F.; Di Nucci, D.; Ferrucci, F.; Palomba, F. | |
| On the adequacy of static analysis warnings with respect to code smell prediction | 1-gen-2022 | Pecorelli, F.; Lujan, S.; Lenarduzzi, V.; Palomba, F.; De Lucia, A. | |
| On the role of data balancing for machine learning-based code smell detection | 1-gen-2019 | Pecorelli, F.; Di Nucci, D.; De Roover, C.; De Lucia, A. | |
| Predicting The Energy Consumption Level of Java Classes in Android Apps: An Exploratory Analysis | 1-gen-2022 | Iannone, E.; De Stefano, M.; Pecorelli, F.; De Lucia, A. | |
| Refactoring android-specific energy smells: A plugin for android studio | 1-gen-2020 | Iannone, E.; Pecorelli, F.; Di Nucci, D.; Palomba, F.; De Lucia, A. | |
| Refactoring Recommendations Based on the Optimization of Socio-Technical Congruence | 1-gen-2020 | De Stefano, M.; Pecorelli, F.; Tamburri, D. A.; Palomba, F.; De Lucia, A | |
| Software engineering for quantum programming: How far are we? | 1-gen-2022 | De Stefano, M.; Pecorelli, F.; Di Nucci, D.; Palomba, F.; De Lucia, A. |