Predicting Bug-Fixing Time: DistilBERT Versus Google BERT

Author:

Ardimento PasqualeORCID

Publisher

Springer International Publishing

Reference16 articles.

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3. de Almeida, C.D.A., Feijó, D.N., Rocha, L.S.: Studying the impact of continuous delivery adoption on bug-fixing time in apache’s open-source projects. In: 2022 IEEE/ACM 19th International Conference on Mining Software Repositories (MSR). pp. 132–136 (2022). https://doi.org/10.1145/3524842.3528049

4. Ardimento, P., Mele, C.: Using BERT to predict bug-fixing time. In: 2020 IEEE Conference on Evolving and Adaptive Intelligent Systems, EAIS 2020, Bari, Italy, May 27–29, 2020. pp. 1–7. IEEE (2020). https://doi.org/10.1109/EAIS48028.2020.9122781

5. Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent dirichlet allocation. In: Dietterich, T.G., Becker, S., Ghahramani, Z. (eds.) Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, NIPS 2001(December), pp. 3–8, 2001. Vancouver, British Columbia, Canada]. pp. 601–608. MIT Press (2001). https://proceedings.neurips.cc/paper/2001/hash/296472c9542ad4d4788d543508116cbc-Abstract.html

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