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Carlino, F., Diana, A., Ventriglia, A., Piccolo, A., Mocerino, C., Riccardi, F., Bilancia, D., Giotta, F., Antoniol, G., Famiglietti, V., Feliciano, S., Cangiano, R., Lobianco, L., Pellegrino, B., De Vita, F., Ciardiello, F., & Orditura, M. (2022). HER2-Low Status Does Not Affect Survival Outcomes of Patients with Metastatic Breast Cancer (MBC) Undergoing First-Line Treatment with Endocrine Therapy plus Palbociclib: Results of a Multicenter, Retrospective Cohort Study. Cancers, 14(20), 4981 (11 pages). Lien externe
Coviello, C., Romano, S., Scanniello, G., & Antoniol, G. (2022). GASSER: A Multi-Objective Evolutionary Approach for Test Suite Reduction. International Journal of Software Engineering and Knowledge Engineering, 32(2), 193-225. Lien externe
Diana, A., Carlino, F., Buono, G., Antoniol, G., Famiglietti, V., De Angelis, C., Carrano, S., Piccolo, A., De Vita, F., Ciardiello, F., Daniele, B., Arpino, G., & Orditura, M. (2022). Prognostic Relevance of Progesterone Receptor Levels in Early Luminal-Like HER2 Negative Breast Cancer Subtypes: A Retrospective Analysis. Frontiers in Oncology, 12. Lien externe
Humeniuk, D., Antoniol, G., & Khomh, F. (mai 2022). ***AmbieGen tool at the SBST 2022 Tool Competition [Communication écrite]. 15th Search-Based Software Testing Workshop (SBST 2022). Lien externe
Humeniuk, D., Khomh, F., & Antoniol, G. (2022). A search-based framework for automatic generation of testing environments for cyber-physical systems. Information and Software Technology, 149, 106936 (17 pages). Lien externe
Iovino, F., Diana, A., Carlino, F., Ferraraccio, F., Antoniol, G., Fisone, F., Perrone, A., Zito Marino, F., Panarese, I., Tathode, M. S., Caraglia, M., Gatta, G., Ruggiero, R., Parisi, S., De Vita, F., Ciardiello, F., Docimo, L., & Orditura, M. (2022). Expression of c-MET in Estrogen Receptor Positive and HER2 Negative Resected Breast Cancer Correlated with a Poor Prognosis. Journal of Clinical Medicine, 11(23), 6987 (15 pages). Lien externe
Marhaba, M., Merlo, E., Khomh, F., & Antoniol, G. (mai 2022). Identification of out-of-distribution cases of CNN using class-based surprise adequacy [Communication écrite]. IEEE/ACM 1st International Conference on AI Engineering - Software Engineering for AI (CAIN 2022), Pittsburgh, PA, USA. Lien externe
Muse, B. A., Khomh, F., & Antoniol, G. (mars 2022). Do developers refactor data access code? An empirical study [Communication écrite]. IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2022), Honolulu, HI, USA. Lien externe
Muse, B. A., Nagy, C., Cleve, A., Khomh, F., & Antoniol, G. (2022). FIXME: synchronize with database! An empirical study of data access self-admitted technical debt. Empirical Software Engineering, 27(6), 42 pages. Lien externe
Tambon, F., Khomh, F., & Antoniol, G. (2022). A Probabilistic Framework for Mutation Testing in Deep Neural Networks - Models archive Part 1 [Ensemble de données]. Lien externe
Tambon, F., Khomh, F., & Antoniol, G. (2022). A Probabilistic Framework for Mutation Testing in Deep Neural Networks - Models archive Part 2 [Ensemble de données]. Lien externe
Tambon, F., Khomh, F., & Antoniol, G. (2022). A Probabilistic Framework for Mutation Testing in Deep Neural Networks - Models archive Part 3 [Ensemble de données]. Lien externe
Tambon, F., Laberge, G., An, L., Nikanjam, A., Mindom, P. S. N., Pequignot, Y., Khomh, F., Antoniol, G., Merlo, E., & Laviolette, F. (2022). How to certify machine learning based safety-critical systems? A systematic literature review. Automated Software Engineering, 29(2). Lien externe
Zampetti, F., Belias, F., Zid, C., Antoniol, G., & Penta, M. D. (octobre 2022). An Empirical Study on the Fault-Inducing Effect of Functional Constructs in Python [Communication écrite]. IEEE International Conference on Software Maintenance and Evolution (ICSME 2022), Limassol, Cyprus. Lien externe
Zampetti, F., Mudbhari, S., Arnaoudova, V., Di Penta, M., Panichella, S., & Antoniol, G. (2022). Using code reviews to automatically configure static analysis tools. Empirical Software Engineering, 27(1), 30 pages. Lien externe
