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Bhatia, A., Eghan, E. E., Grichi, M., Cavanagh, W. G., Jiang, Z. M., & Adams, B. (2023). Towards a change taxonomy for machine learning pipelines Empirical study of ML pipelines and forks related to academic publications. Empirical Software Engineering, 28(3), 60 (34 pages). Lien externe
Lyu, Y., Li, H., Sayagh, M., Jiang, Z. M., & Hassan, A. E. (2021). An empirical study of the impact of data splitting decisions on the performance of AiOps solutions. ACM Transactions on Software Engineering and Methodology, 30(4), 1-38. Lien externe
Morovati, M. M., Nikanjam, A., Tambon, F., Khomh, F., & Jiang, Z. M. (2024). Bug characterization in machine learning-based systems. Empirical Software Engineering, 29(1), 14 (29 pages). Lien externe
Morovati, M. M., Nikanjam, A., Khomh, F., & Jiang, Z. M. (2023). Bugs in machine learning-based systems: a faultload benchmark. Empirical Software Engineering, 28(3), 33 pages. Lien externe
Shang, W., Jiang, Z. M., Adams, B., Hassan, A. E., Godfrey, M. W., Nasser, M., & Flora, P. (2014). An exploratory study of the evolution of communicated information about the execution of large software systems. Journal of Software: Evolution and Process, 26(1), 3-26. Lien externe
Shang, W., Jiang, Z. M., Hemmati, H., Adams, B., Hassan, A. E., & Martin, P. (mai 2013). Assisting big data analytics developers when cloud deploying hadoop applications [Communication écrite]. 35th International Conference on Software Engineering (ICSE 2013), San Francisco, CA, USA. 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
