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Badran, K., Cote, P.-O., Kolopanis, A., Bouchoucha, R., Collante, A., Costa, D. E., Shihab, E., & Khomh, F. (2023). Can Ensembling Preprocessing Algorithms Lead to Better Machine Learning Fairness? Computer, 56(4), 71-79. Lien externe
Chowdhury, M. A. R., Abdalkareem, R., Shihab, E., & Adams, B. (2022). On the Untriviality of Trivial Packages: An Empirical Study of npm JavaScript Packages. IEEE Transactions on Software Engineering, 48(8), 2695-2708. Lien externe
Kamei, Y., Shihab, E., Adams, B., Hassan, A. E., Mockus, A., Sinha, A., & Ubayashi, N. (2013). A large-scale empirical study of just-in-time quality assurance. IEEE Transactions on Software Engineering, 39(6), 757-773. Lien externe
Shihab, E., Kamei, Y., Adams, B., & Hassan, A. E. (2013). Is Lines of Code a Good Measure of Effort in Effort-Aware Models? Information and Software Technology, 55(11), 1981-1993. Lien externe
Shihab, E., Ihara, A., Kamei, Y., Ibrahim, W. M., Ohira, M., Adams, B., Hassan, A. E., & Matsumoto, K.-I. (2013). Studying re-opened bugs in open source software. Empirical Software Engineering, 18(5), 1005-1042. Lien externe
Shihab, E., Hassan, A. E., Adams, B., & Jiang, Z. M. (novembre 2012). An industrial study on the risk of software changes [Communication écrite]. 20th ACM SIGSOFT International Symposium on the Foundations of Software Engineering (FSE 2012), Cary, NC, United states. Lien externe
Yin Ho, S. C., Majdinasab, V., Islam, M., Costa, D. E., Shihab, E., Khomh, F., Nadi, S., & Raza, M. (octobre 2023). An Empirical Study on Bugs Inside PyTorch: A Replication Study [Communication écrite]. 39th IEEE International Conference on Software Maintenance and Evolution (ICSME 2023), Bogota, Colombia. Lien externe
