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Marco Castelluccio
Marco Castelluccio
Università Federico II di Napoli and Mozilla
Bestätigte E-Mail-Adresse bei unina.it
Titel
Zitiert von
Zitiert von
Jahr
Land use classification in remote sensing images by convolutional neural networks
M Castelluccio, G Poggi, C Sansone, L Verdoliva
arXiv preprint arXiv:1508.00092, 2015
7752015
Understanding flaky tests: The developer’s perspective
M Eck, F Palomba, M Castelluccio, A Bacchelli
Proceedings of the 2019 27th ACM Joint Meeting on European Software …, 2019
1462019
What makes a code change easier to review: an empirical investigation on code change reviewability
A Ram, AA Sawant, M Castelluccio, A Bacchelli
Proceedings of the 2018 26th ACM Joint Meeting on European Software …, 2018
492018
Automatically analyzing groups of crashes for finding correlations
M Castelluccio, C Sansone, L Verdoliva, G Poggi
Proceedings of the 2017 11th Joint Meeting on Foundations of Software …, 2017
252017
Training convolutional neural networks for semantic classification of remote sensing imagery
M Castelluccio, G Poggi, C Sansone, L Verdoliva
2017 Joint Urban Remote Sensing Event (JURSE), 1-4, 2017
232017
Why are some bugs non-reproducible?:–an empirical investigation using data fusion–
MM Rahman, F Khomh, M Castelluccio
2020 IEEE international conference on software maintenance and evolution …, 2020
182020
An empirical study of patch uplift in rapid release development pipelines
M Castelluccio, L An, F Khomh
Empirical Software Engineering 24, 3008-3044, 2019
182019
Land use classification in remote sensing images by convolutional neural networks, 2015
M Castelluccio, G Poggi, C Sansone, L Verdoliva
arXiv preprint arXiv:1508.00092, 0
16
rust-code-analysis: A rust library to analyze and extract maintainability information from source codes
L Ardito, L Barbato, M Castelluccio, R Coppola, C Denizet, S Ledru, ...
SoftwareX 12, 100635, 2020
142020
Is it safe to uplift this patch?: An empirical study on mozilla firefox
M Castelluccio, L An, F Khomh
2017 IEEE international conference on software maintenance and evolution …, 2017
72017
SZZ in the time of pull requests
F Petrulio, D Ackermann, E Fregnan, G Calikli, M Castelluccio, S Ledru, ...
arXiv preprint arXiv:2209.03311, 2022
52022
An empirical study of dll injection bugs in the firefox ecosystem
L An, M Castelluccio, F Khomh
Empirical Software Engineering 24, 1799-1822, 2019
52019
Land use classification. n
M Castelluccio, G Poggi, C Sansone, L Verdoliva
Remote Sensing Images by Convolutional Neural Networks, 0
5
Works for me! cannot reproduce–a large scale empirical study of non-reproducible bugs
MM Rahman, F Khomh, M Castelluccio
Empirical Software Engineering 27 (5), 111, 2022
42022
Why did this reviewed code crash? An empirical study of mozilla firefox
L An, F Khomh, S Mcintosh, M Castelluccio
2018 25th Asia-Pacific Software Engineering Conference (APSEC), 396-405, 2018
32018
Mind the Gap: What Working With Developers on Fuzz Tests Taught Us About Coverage Gaps
C Brandt, M Castelluccio, C Holler, J Kratzer, A Zaidman, A Bacchelli
Proceedings of the International Conference on Software Engineering-Software …, 2024
22024
Data and Material for “What Makes A Code Change Easier To Review?”
A Ram, AA Sawant, M Castelluccio, A Bacchelli
22018
What Makes a Code Change Easier to Review
A Ram, AA Sawant, M Castelluccio, A Bacchelli
An Empirical Investigation on Code Change Reviewability. ESEC/FSE. DOI …, 2018
22018
Predicting the Impact of Crashes Across Release Channels
S Mujahid, DE Costa, M Castelluccio
arXiv preprint arXiv:2401.13667, 2024
2024
Why are Some Bugs Non-Reproducible? An Empirical Investigation using Data Fusion
M Masudur Rahman, F Khomh, M Castelluccio
arXiv e-prints, arXiv: 2108.05316, 2021
2021
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