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Ikama, A., Du, V., Belias, P., Muse, B. A., Khomh, F., & Hamdaqa, M. (octobre 2022). Revisiting the Impact of Anti-patterns on Fault-Proneness: A Differentiated Replication [Communication écrite]. 22nd IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM 2022), Limassol, Cyprus. Lien externe
Jebnoun, H., Rahman, M. S., Khomh, F., & Muse, B. A. (2022). Clones in deep learning code: what, where, and why? Empirical Software Engineering, 27(4). Lien externe
Muse, B. A. (2022). Data-Access Technical Debt: Specification, Refactoring, and Impact Analysis [Thèse de doctorat, Polytechnique Montréal]. Disponible
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
