  | DE ALENCAR CARVALHO, L. M., DEGIOVANNI, R. G., CORDY, M., Aguirre, N., Traon, Y. L., & PAPADAKIS, M. (2024). SPECBCFuzz: Fuzzing LTL Solvers with Boundary Conditions. In Proceedings - 2024 ACM/IEEE 44th International Conference on Software Engineering, ICSE 2024 (pp. 12). IEEE Computer Society. doi:10.1145/3597503.3639087  Peer reviewed |
 | 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 verified by ORBi |
 | 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 |
 | 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., 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 |
 | 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 |