Status Quo and Problems of Requirements Engineering for Machine Learning: Results from an International Survey-Reference-Cited by-同舟云学术

Status Quo and Problems of Requirements Engineering for Machine Learning: Results from an International Survey

Published:2023-12-02 Issue: Volume: Page:159-174
ISSN:0302-9743
Container-title:Product-Focused Software Process Improvement
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Author:

Alves Antonio Pedro Santos,Kalinowski Marcos,Giray Görkem,Mendez Daniel,Lavesson Niklas,Azevedo Kelly,Villamizar Hugo,Escovedo Tatiana,Lopes Helio,Biffl Stefan,Musil Jürgen,Felderer Michael,Wagner Stefan,Baldassarre Teresa,Gorschek Tony

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-49266-2_11

Reference30 articles.

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2. Amershi, S., et al.: Software engineering for machine learning: a case study. In: 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Practice, pp. 291–300. IEEE (2019)

3. Challa, H., Niu, N., Johnson, R.: Faulty requirements made valuable: on the role of data quality in deep learning. In: 2020 IEEE 7th International Workshop on Artificial Intelligence for Requirements Engineering, pp. 61–69. IEEE (2020)

4. Dalpiaz, F., Niu, N.: Requirements engineering in the days of artificial intelligence. IEEE Softw. 37(4), 7–10 (2020)

5. Efron, B., Tibshirani, R.J.: An Introduction to the Bootstrap. Chapman & Hall/CRC (1993)

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