Fabiano Pecorelli
Fabiano Pecorelli
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Comparing heuristic and machine learning approaches for metric-based code smell detection
F Pecorelli, F Palomba, D Di Nucci, A De Lucia
2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC …, 2019
372019
Developer-driven code smell prioritization
F Pecorelli, F Palomba, F Khomh, A De Lucia
Proceedings of the 17th International Conference on Mining Software …, 2020
132020
A large empirical assessment of the role of data balancing in machine-learning-based code smell detection
F Pecorelli, D Di Nucci, C De Roover, A De Lucia
Journal of Systems and Software 169, 110693, 2020
122020
On the role of data balancing for machine learning-based code smell detection
F Pecorelli, D Di Nucci, C De Roover, A De Lucia
Proceedings of the 3rd ACM SIGSOFT international workshop on machine …, 2019
122019
Testing of mobile applications in the wild: A large-scale empirical study on android apps
F Pecorelli, G Catolino, F Ferrucci, A De Lucia, F Palomba
Proceedings of the 28th International Conference on Program Comprehension …, 2020
92020
VITRuM: A Plug-In for the Visualization of Test-Related Metrics
F Pecorelli, G Di Lillo, F Palomba, A De Lucia
Proceedings of the International Conference on Advanced Visual Interfaces, 1-3, 2020
52020
Splicing community patterns and smells: A preliminary study
M De Stefano, F Pecorelli, DA Tamburri, F Palomba, A De Lucia
Proceedings of the IEEE/ACM 42nd International Conference on Software …, 2020
52020
Just-In-Time Test Smell Detection and Refactoring: The DARTS Project
S Lambiase, A Cupito, F Pecorelli, A De Lucia, F Palomba
Proceedings of the 28th International Conference on Program Comprehension …, 2020
42020
Refactoring android-specific energy smells: A plugin for android studio
E Iannone, F Pecorelli, D Di Nucci, F Palomba, A De Lucia
Proceedings of the 28th International Conference on Program Comprehension …, 2020
32020
The Relation of Test-Related Factors to Software Quality: A Case Study on Apache Systems
F Pecorelli, F Palomba, A De Lucia
Empirical Software Engineering 26 (2), 1-42, 2021
22021
cASpER: A Plug-in for Automated Code Smell Detection and Refactoring
M De Stefano, MS Gambardella, F Pecorelli, F Palomba, A De Lucia
Proceedings of the International Conference on Advanced Visual Interfaces, 1-3, 2020
22020
Adaptive selection of classifiers for bug prediction: A large-scale empirical analysis of its performances and a benchmark study
F Pecorelli, D Di Nucci
Science of Computer Programming 205, 102611, 2021
12021
A preliminary study on the adequacy of static analysis warnings with respect to code smell prediction
S Lujan, F Pecorelli, F Palomba, A De Lucia, V Lenarduzzi
Proceedings of the 4th ACM SIGSOFT International Workshop on Machine …, 2020
12020
Test-related factors and post-release defects: an empirical study
F Pecorelli
Proceedings of the 2019 27th ACM Joint Meeting on European Software …, 2019
12019
Impacts of Software Community Patterns on Process and Product: An Empirical Study
M De Stefano, E Iannone, F Pecorelli, DA Tamburri
Science of Computer Programming, 102731, 2021
2021
Comparing within-and cross-project machine learning algorithms for code smell detection
M De Stefano, F Pecorelli, F Palomba, A De Lucia
Proceedings of the 5th International Workshop on Machine Learning Techniques …, 2021
2021
Refactoring Recommendations Based on the Optimization of Socio-Technical Congruence
M De Stefano, F Pecorelli, DA Tamburri, F Palomba, A De Lucia
2020 IEEE International Conference on Software Maintenance and Evolution …, 2020
2020
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