| 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 | 854 | 2015 |
| 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 | 220 | 2019 |
| 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 | 68 | 2018 |
| 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 | 29 | 2017 |
| 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 | 28 | 2020 |
| An empirical study of patch uplift in rapid release development pipelines M Castelluccio, L An, F Khomh Empirical Software Engineering 24 (5), 3008-3044, 2019 | 24 | 2019 |
| 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 | 22 | 2020 |
| 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 | 22 | 2017 |
| Land use classification in remote sensing images by convolutional neural networks, 2015 M Castelluccio, G Poggi, C Sansone, L Verdoliva ArXiv150800092 374, 0 | 21 | |
| 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 | 13 | 2022 |
| An empirical study of dll injection bugs in the firefox ecosystem L An, M Castelluccio, F Khomh Empirical Software Engineering 24 (4), 1799-1822, 2019 | 12 | 2019 |
| 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 46th International Conference on Software Engineering …, 2024 | 10 | 2024 |
| 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 | 8 | 2017 |
| 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 | 7 | 2022 |
| Unveiling the potential of a conversational agent in developer support: Insights from mozilla’s pdf. js project J Correia, MC Nicholson, D Coutinho, C Barbosa, M Castelluccio, ... Proceedings of the 1st ACM International Conference on AI-Powered Software …, 2024 | 6 | 2024 |
| 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 | 5 | 2018 |
| 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 | 5 | 2018 |
| Automated generation of issue-reproducing tests by combining llms and search-based testing K Kitsios, M Castelluccio, A Bacchelli arXiv preprint arXiv:2509.01616, 2025 | 3 | 2025 |
| Impact of LLM-based review comment generation in practice: A mixed open-/closed-source user study D Olewicki, L Da Silva, S Mujahid, A Amini, B Mah, M Castelluccio, ... arXiv preprint arXiv:2411.07091, 2024 | 2 | 2024 |
| Data and Material for “What Makes A Code Change Easier To Review?” A Ram, AA Sawant, M Castelluccio, A Bacchelli | 2 | 2018 |
