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Documents publiés en "2021"

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Nombre de documents: 9

Département de génie informatique et génie logiciel

El aoun, M. R., Li, H., Khomh, F., & Openja, M. (septembre 2021). Understanding Quantum Software Engineering Challenges An Empirical Study on Stack Exchange Forums and GitHub Issues [Communication écrite]. IEEE International Conference on Software Maintenance and Evolution (ICSME 2021), Luxembourg, Netherlands. Lien externe

Gujral, H., Lal, S., & Li, H. (2021). An exploratory semantic analysis of logging questions. Journal of Software: Evolution and Process, 33(7), 35 pages. Lien externe

Li, H., Shang, W., Adams, B., Sayagh, M., & Hassan, A. E. (2021). A qualitative study of the benefits and costs of logging from developers' perspectives. IEEE Transactions on Software Engineering, 47(12), 2858-2873. Lien externe

Li, H., Zhang, H., Wang, S., & Hassan, A. E. (2021). Studying the Practices of Logging Exception Stack Traces in Open-Source Software Projects. IEEE Transactions on Software Engineering, 19 pages. Lien externe

Li, Z., Li, H., Chen, T.-H. P., & Shang, W. (mai 2021). DeepLV: Suggesting log levels using ordinal based neural networks [Communication écrite]. 43rd International Conference on Software Engineering (ICSE 2021) (12 pages). Lien externe

Liao, L., Chen, J., Li, H., Zeng, Y., Shang, W., Sporea, C., Toma, A., & Sajedi, S. (2021). Locating Performance Regression Root Causes in the Field Operations of Web-based Systems: An Experience Report. IEEE Transactions on Software Engineering, 22 pages. Lien externe

Liao, L., Chen, J., Li, H., Zeng, Y., Shang, W., Sporea, C., Toma, A., & Sajedi, S. (2021). Replication package - Locating Performance Regression Root Causes in the Field for Web-based Systems [Ensemble de données]. Lien externe

Liao, L., Chen, J., Li, H., Zeng, Y., Shang, W., Sporea, C., Toma, A., & Sajedi, S. (2021). TSE2021 Replication Package [Ensemble de données]. 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

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