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Documents publiés en "2020"

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Nombre de documents: 24

A

Abidi, M., & Khomh, F. (juillet 2020). Towards the definition of patterns and code smells for multi-language systems [Communication écrite]. European Conference on Pattern Languages of Programs (EuroPLoP 2020), New York, NY, USA (13 pages). Lien externe

Abidi, M., Openja, M., & Khomh, F. (juin 2020). Multi-language design smells : a backstage perspective [Communication écrite]. 17th International Conference on Mining Software Repositories (MSR 2020), Seoul, Republic of Korea. Lien externe

Adams, B., & Khomh, F. (2020). The Diversity Crisis of Software Engineering for Artificial Intelligence. IEEE Software, 37(5), 104-108. Lien externe

B

Barbez, A., Khomh, F., & Guéhéneuc, Y.-G. (2020). A machine-learning based ensemble method for anti-patterns detection. Journal of Systems and Software, 161, 11 pages. Lien externe

Ben Braiek, H., & Khomh, F. (2020). On testing machine learning programs. Journal of Systems and Software, 164, 110542 (18 pages). Lien externe

Berhe, S., Maynard, M., & Khomh, F. (avril 2020). Software Release Patterns When is it a good time to update a software component? [Communication écrite]. 11th International Conference on Ambient Systems, Networks and Technologies (ANT 2020) and 3rd International Conference on Emerging Data and Industry 4.0 (EDI40 2020), Warsaw, Poland. Publié dans Procedia Computer Science, 170. Lien externe

F

Firouzi, E., Sami, A., Khomh, F., & Uddin, G. (octobre 2020). On the use of C# Unsafe Code Context: An Empirical Study of Stack Overflow [Communication écrite]. 14th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM 2020), Bari, Italy (6 pages). Lien externe

J

Jebnoun, H., Ben Braiek, H., Rahman, M. M., & Khomh, F. (juin 2020). The scent of deep learning code : an empirical study [Communication écrite]. 17th International Conference on Mining Software Repositories (MSR 2020), Seoul, Republic of Korea. Lien externe

M

Morales, R., Khomh, F., & Antoniol, G. (2020). RePOR: Mimicking humans on refactoring tasks. Are we there yet? Empirical Software Engineering, 25(4), 2960-2996. Lien externe

Muse, B. A., Rahman, M. M., Nagy, C., Cleve, A., Khomh, F., & Antoniol, G. (juin 2020). On the prevalence, impact and evolution of SQL Code smells in data-intensive systems [Communication écrite]. 17th International Conference on Mining Software Repositories (MSR 2020), Seoul, Republic of Korea. Lien externe

O

Openja, M., Adams, B., & Khomh, F. (septembre 2020). Analysis of Modern Release Engineering Topics : – A Large-Scale Study using StackOverflow – [Communication écrite]. IEEE International Conference on Software Maintenance and Evolution (ICSME 2020), Adelaide, Australia. Lien externe

P

Pecorelli, F., Palomba, F., Khomh, F., & De Lucia, A. (juin 2020). Developer-driven code smell prioritization [Communication écrite]. 17th International Conference on Mining Software Repositories (MSR 2020), Seoul, Republic of Korea. Lien externe

Politowski, C., Khomh, F., Romano, S., Scanniello, G., Petrillo, F., Guéhéneuc, Y.-G., & Maiga, A. (2020). A large scale empirical study of the impact of Spaghetti Code and Blob anti-patterns on program comprehension. Information and Software Technology, 122, 14 pages. Lien externe

Politowski, C., Khomh, F., Romano, S., Scanniello, G., Petrillo, F., Guéhéneuc, Y.-G., & Maiga, A. (2020). A Large Scale Empirical Study of the Impact of Spaghetti Code and Blob Anti-patterns on Program Comprehension [Ensemble de données]. Lien externe

R

Rahman, M. M., Khomh, F., & Castelluccio, M. (septembre 2020). Why are Some Bugs Non-Reproducible? : An Empirical Investigation using Data Fusion [Communication écrite]. IEEE International Conference on Software Maintenance and Evolution (ICSME 2020). Lien externe

S

Soualhia, M., Khomh, F., & Tahar, S. (2020). A Dynamic and Failure-aware Task Scheduling Framework for Hadoop. IEEE Transactions on Cloud Computing, 8(2), 553-569. Lien externe

T

Tiwari, D., Washizaki, H., Fukazawa, Y., Fukuoka, T., Tamaki, J., Hosotani, N., Kohama, M., Guéhéneuc, Y.-G., & Khomh, F. (mai 2020). Commit-defect and architectural metrics-based quality assessment of C language [Communication écrite]. 15th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2020). Lien externe

U

Uddin, G., Khomh, F., & Roy, C. K. (2020). Mining API usage scenarios from stack overflow. Information and Software Technology, 122, 16 pages. Lien externe

V

Verdi, M., Sami, A., Akhondali, J., Khomh, F., Uddin, G., & Karami Motlagh, A. (2020). An Empirical Study of C++ Vulnerabilities in Crowd-Sourced Code Examples. IEEE Transactions on Software Engineering, 48(5), 1497-1514. Lien externe

W

Washizaki, H., Khomh, F., & Guéhéneuc, Y.-G. (septembre 2020). Software engineering patterns for machine learning applications (SEP4MLA) [Communication écrite]. 9th Asian Conference on Pattern Languages of Program in 2020 (AsianPLoP 2020), Taipei, Taiwan (10 pages). Non disponible

Washizaki, H., Khomh, F., Guéhéneuc, Y.-G., Takeuchi, H., Okuda, S., Natori, N., & Shioura, N. (octobre 2020). Software Engineering Patterns for Machine Learning Applications (SEP4MLA) - Part 2 [Communication écrite]. 27th Conference on Pattern Languages of Programs in 2020 (PLoP' 2020) (10 pages). Non disponible

Washizaki, H., Takeuchi, H., Khomh, F., Natori, N., Doi, T., & Okuda, S. (septembre 2020). Practitioners' insights on machine-learning software engineering design patterns: a preliminary study [Communication écrite]. IEEE International Conference on Software Maintenance and Evolution (ICSME 2020). Lien externe

X

Xu, B., An, L., Thung, F., Khomh, F., & Lo, D. (2020). Why reinventing the wheels? An empirical study on library reuse and re-implementation. Empirical Software Engineering, 25(1), 755-789. Lien externe

Z

Zid, C., Humeniuk, D., Khomh, F., & Antoniol, G. (juin 2020). Double cycle hybrid testing of hybrid distributed IoT system [Communication écrite]. IEEE/ACM 42nd International Conference on Software Engineering Workshops (ICSEW 2020), Seoul, Republic of Korea. Lien externe

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