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Fabiano Pecorelli
Fabiano Pecorelli
Postdoctoral Researcher, Tampere University
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα tuni.fi - Αρχική σελίδα
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Παρατίθεται από
Παρατίθεται από
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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
562019
Developer-driven code smell prioritization
F Pecorelli, F Palomba, F Khomh, A De Lucia
Proceedings of the 17th International Conference on Mining Software …, 2020
342020
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
312020
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
192019
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
152020
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
112020
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
102020
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
82021
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
82020
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
52021
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
52020
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
52020
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
PANDORA: Continuous mining software repository and dataset generation
H Nguyen, F Lomio, F Pecorelli, V Lenarduzzi
EEE International Conference on Software Analysis, Evolution and …, 2022
32022
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
32021
Test-related factors and post-release defects: an empirical study
F Pecorelli
Proceedings of the 2019 27th ACM Joint Meeting on European Software …, 2019
32019
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 214, 102731, 2022
22022
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
22020
On the adequacy of static analysis warnings with respect to code smell prediction
F Pecorelli, S Lujan, V Lenarduzzi, F Palomba, A De Lucia
Empirical Software Engineering 27 (3), 1-44, 2022
12022
Software engineering for quantum programming: How far are we?
M De Stefano, F Pecorelli, D Di Nucci, F Palomba, A De Lucia
Journal of Systems and Software 190, 111326, 2022
2022
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