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DEGIOVANNI Renzo Gaston

Main Referenced Co-authors
PAPADAKIS, Michail  (9)
LE TRAON, Yves  (6)
Aguirre, Nazareno (5)
GARG, Aayush  (5)
CORDY, Maxime  (4)
Main Referenced Keywords
Mutation Testing (3); Software Testing (2); CodeBERT (1); Continuous Integration (1); Empirical Comparison (1);
Main Referenced Unit & Research Centers
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > SerVal - Security, Reasoning & Validation (2)
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Security Design and Validation Research Group (SerVal) (1)
Main Referenced Disciplines
Computer science (11)

Publications (total 11)

The most downloaded
190 downloads
Molina, F., Degiovanni, R. G., Ponzio, P., Regis, G., Aguirre, N., & Frias, M. F. (2019). Training binary classifiers as data structure invariants. In Proceedings of the 41st International Conference on Software Engineering ICSE 2019, Montreal, QC, Canada, May 25-31, 2019 (pp. 759 - 770). doi:10.1109/ICSE.2019.00084 https://hdl.handle.net/10993/41037

The most cited

11 citations (Scopus®)

Molina, F., Degiovanni, R. G., Ponzio, P., Regis, G., Aguirre, N., & Frias, M. F. (2019). Training binary classifiers as data structure invariants. In Proceedings of the 41st International Conference on Software Engineering ICSE 2019, Montreal, QC, Canada, May 25-31, 2019 (pp. 759 - 770). doi:10.1109/ICSE.2019.00084 https://hdl.handle.net/10993/41037

Garg, A., Ojdanic, M., Degiovanni, R. G., Titcheu Chekam, T., Papadakis, M., & Le Traon, Y. (2023). Cerebro: Static Subsuming Mutant Selection. IEEE Transactions on Software Engineering. doi:10.1109/TSE.2022.3140510
Peer reviewed

Ojdanic, M., Khanfir, A., Garg, A., Degiovanni, R. G., Papadakis, M., & Le Traon, Y. (2023). On Comparing Mutation Testing Tools through Learning-based Mutant Selection. In On Comparing Mutation Testing Tools through Learning-based Mutant Selection (pp. 10). doi:10.1109/AST58925.2023.00008
Peer reviewed

Ojdanic, M., Garg, A., Khanfir, A., Degiovanni, R. G., Papadakis, M., & Le Traon, Y. (2023). Syntactic Vs. Semantic similarity of Artificial and Real Faults in Mutation Testing Studies. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/49190. doi:10.1109/TSE.2023.3277564

Carvalho, L., DEGIOVANNI, R. G., Brizzio, M. A., CORDY, M., Aguirre, N., LE TRAON, Y., & PAPADAKIS, M. (2023). ACoRe: Automated Goal-Conflict Resolution. 26th International Conference on Fundamental Approaches to Software Engineering (FASE), 13991, 3–25. doi:10.1007/978-3-031-30826-0_1
Peer reviewed

GARG, A., DEGIOVANNI, R. G., Molina, F., CORDY, M., Aguirre, N., PAPADAKIS, M., & Traon, Y. (2023). Enabling Efficient Assertion Inference. International Symposium on Software Reliability Engineering (ISSRE), 623–634. doi:10.1109/ISSRE59848.2023.00039
Peer reviewed

Brizzio, M. A., CORDY, M., PAPADAKIS, M., Sánchez, C. S., Aguirre, N., & DEGIOVANNI, R. G. (2023). Automated Repair of Unrealisable LTL Specifications Guided by Model Counting. Genetic and Evolutionary Computation Conference (GECCO), 1499–1507. doi:10.1145/3583131.3590454
Peer reviewed

Garg, A., Degiovanni, R. G., Jimenez, M., Cordy, M., Papadakis, M., & Le Traon, Y. (2022). Learning from what we know: How to perform vulnerability prediction using noisy historical data. Empirical Software Engineering. doi:10.1007/s10664-022-10197-4
Peer Reviewed verified by ORBi

Ojdanic, M., Soremekun, E., Degiovanni, R. G., Papadakis, M., & Le Traon, Y. (2022). Mutation Testing in Evolving Systems: Studying the relevance of mutants to code evolution. ACM Transactions on Software Engineering and Methodology. doi:10.1145/3530786
Peer Reviewed verified by ORBi

Degiovanni, R. G., & Papadakis, M. (2022). µBert: Mutation Testing using Pre-Trained Language Models. In R. G. Degiovanni & M. Papadakis, µBert: Mutation Testing using Pre-Trained Language Models (pp. 160--169). IEEE. doi:10.1109/ICSTW55395.2022.00039
Peer reviewed

Molina, F., Cornejo, C., Degiovanni, R. G., Regis, G., Castro, P. F., Aguirre, N., & Frias, M. F. (2019). An evolutionary approach to translating operational specifications into declarative specifications. Science of Computer Programming, 181, 47--63. doi:10.1016/j.scico.2019.05.006
Peer Reviewed verified by ORBi

Molina, F., Degiovanni, R. G., Ponzio, P., Regis, G., Aguirre, N., & Frias, M. F. (2019). Training binary classifiers as data structure invariants. In Proceedings of the 41st International Conference on Software Engineering ICSE 2019, Montreal, QC, Canada, May 25-31, 2019 (pp. 759 - 770). doi:10.1109/ICSE.2019.00084
Peer reviewed

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