A Zero-Shot Learning Approach to Classifying Requirements: A Preliminary Study

Author:

Alhoshan WaadORCID,Zhao LipingORCID,Ferrari AlessioORCID,Letsholo Keletso J.ORCID

Publisher

Springer International Publishing

Reference24 articles.

1. Berry, D.M.: Empirical evaluation of tools for hairy requirements engineering tasks. Empir. Softw. Eng. 26(6), 1–77 (2021). https://doi.org/10.1007/s10664-021-09986-0

2. Brown, T.B., et al.: Language models are few-shot learners. arXiv preprint arXiv:2005.14165 (2020)

3. Dabrowski, J., Letier, E., Perini, A., Susi, A.: App review analysis for software engineering: a systematic literature review. University College London, Technical report (2020)

4. Dalpiaz, F., Dell’Anna, D., Aydemir, F.B., Çevikol, S.: Requirements classification with interpretable machine learning and dependency parsing. In: RE 2019, pp. 142–152. IEEE (2019)

5. Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)

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