Sfoglia per Autore
Comparing heuristic and machine learning approaches for metric-based code smell detection
2019 Pecorelli, Fabiano; Palomba, F.; Di Nucci, D.; De Lucia, A.
On the role of data balancing for machine learning-based code smell detection
2019 Pecorelli, F.; Di Nucci, D.; De Roover, C.; De Lucia, A.
Splicing Community Patterns and Smells: A Preliminary Study
2020 De Stefano, M.; Pecorelli, F.; Tamburri, D. A.; Palomba, F.; De Lucia, A.
VITRuM: A Plug-In for the Visualization of Test-Related Metrics
2020 Pecorelli, F.; Di Lillo, G.; Palomba, F.; De Lucia, A.
Developer-Driven Code Smell Prioritization
2020 Pecorelli, F.; Palomba, F.; Khomh, F.; De Lucia, A.
CASpER: A Plug-in for Automated Code Smell Detection and Refactoring
2020 De Stefano, M.; Gambardella, M. S.; Pecorelli, F.; Palomba, F.; De Lucia, A.
A large empirical assessment of the role of data balancing in machine-learning-based code smell detection
2020 Pecorelli, F.; Di Nucci, D.; De Roover, C.; De Lucia, A.
Just-in-time test smell detection and refactoring: The DARTS project
2020 Lambiase, S.; Cupito, A.; Pecorelli, F.; De Lucia, A.; Palomba, F.
Refactoring Recommendations Based on the Optimization of Socio-Technical Congruence
2020 De Stefano, M.; Pecorelli, F.; Tamburri, D. A.; Palomba, F.; De Lucia, A
Refactoring android-specific energy smells: A plugin for android studio
2020 Iannone, E.; Pecorelli, F.; Di Nucci, D.; Palomba, F.; De Lucia, A.
Testing of mobile applications in the wild: A large-scale empirical study on android apps
2020 Pecorelli, F.; Catolino, G.; Ferrucci, F.; De Lucia, A.; Palomba, F.
A preliminary study on the adequacy of static analysis warnings with respect to code smell prediction
2020 Lujan, S.; Pecorelli, F.; Palomba, F.; De Lucia, A.; Lenarduzzi, V.
The Relation of Test-Related Factors to Software Quality: A Case Study on Apache Systems
2021 Pecorelli, Fabiano; Palomba, Fabio; DE LUCIA, Andrea
Comparing within-and cross-project machine learning algorithms for code smell detection
2021 De Stefano, M.; Pecorelli, F.; Palomba, F.; De Lucia, A.
Adaptive selection of classifiers for bug prediction: A large-scale empirical analysis of its performances and a benchmark study
2021 Pecorelli, F.; Di Nucci, D.
On the adequacy of static analysis warnings with respect to code smell prediction
2022 Pecorelli, F.; Lujan, S.; Lenarduzzi, V.; Palomba, F.; De Lucia, A.
Software engineering for quantum programming: How far are we?
2022 De Stefano, M.; Pecorelli, F.; Di Nucci, D.; Palomba, F.; De Lucia, A.
“There and Back Again?” On the Influence of Software Community Dispersion Over Productivity
2022 Lambiase, Stefano; Catolino, Gemma; Pecorelli, Fabiano; Tamburri, Damian A.; Palomba, Fabio; Van Den Heuvel, Willem-Jan; Ferrucci, Filomena
A Multivocal Literature Review of MLOps Tools and Features
2022 Recupito, Gilberto; Pecorelli, Fabiano; Catolino, Gemma; Moreschini, Sergio; Nucci, Dario Di; Palomba, Fabio; Tamburri, Damian A.
Software testing and Android applications: a large-scale empirical study
2022 Pecorelli, F.; Catolino, G.; Ferrucci, F.; De Lucia, A.; Palomba, F.
| Titolo | Data di pubblicazione | Autore(i) | File |
|---|---|---|---|
| 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. | |
| 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. | |
| Splicing Community Patterns and Smells: A Preliminary Study | 1-gen-2020 | De Stefano, M.; Pecorelli, F.; Tamburri, D. A.; Palomba, F.; De Lucia, A. | |
| VITRuM: A Plug-In for the Visualization of Test-Related Metrics | 1-gen-2020 | Pecorelli, F.; Di Lillo, G.; Palomba, F.; De Lucia, A. | |
| Developer-Driven Code Smell Prioritization | 1-gen-2020 | Pecorelli, F.; Palomba, F.; Khomh, F.; De Lucia, A. | |
| 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. | |
| 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. | |
| 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. | |
| 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 | |
| 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. | |
| Testing of mobile applications in the wild: A large-scale empirical study on android apps | 1-gen-2020 | Pecorelli, F.; Catolino, G.; Ferrucci, F.; De Lucia, A.; Palomba, F. | |
| 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. | |
| The Relation of Test-Related Factors to Software Quality: A Case Study on Apache Systems | 1-gen-2021 | Pecorelli, Fabiano; Palomba, Fabio; DE LUCIA, Andrea | |
| 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. | |
| 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. | |
| 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. | |
| 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. | |
| “There and Back Again?” On the Influence of Software Community Dispersion Over Productivity | 1-gen-2022 | Lambiase, Stefano; Catolino, Gemma; Pecorelli, Fabiano; Tamburri, Damian A.; Palomba, Fabio; Van Den Heuvel, Willem-Jan; Ferrucci, Filomena | |
| 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. | |
| Software testing and Android applications: a large-scale empirical study | 1-gen-2022 | Pecorelli, F.; Catolino, G.; Ferrucci, F.; De Lucia, A.; Palomba, F. |
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