Automated testing of software that uses machine learning APIs

Author:

Wan Chengcheng1,Liu Shicheng1,Xie Sophie2,Liu Yifan1,Hoffmann Henry1,Maire Michael1,Lu Shan1

Affiliation:

1. University of Chicago

2. Whitney Young High School

Funder

ARO

DOE Early Career Award

NSF

Publisher

ACM

Reference108 articles.

1. Google "Google cloud ai." Online document https://cloud.google.com/products/ai 2020. Google "Google cloud ai." Online document https://cloud.google.com/products/ai 2020.

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3. Microsoft "Microsoft azure cognitive services." Online document https://azure.microsoft.com/en-us/services/cognitive-services 2020. Microsoft "Microsoft azure cognitive services." Online document https://azure.microsoft.com/en-us/services/cognitive-services 2020.

4. IBM "Ibm watson." Online document https://www.ibm.com/watson 2020. IBM "Ibm watson." Online document https://www.ibm.com/watson 2020.

5. S. Amershi , A. Begel , C. Bird , R. DeLine , H. Gall , E. Kamar , N. Nagappan , B. Nushi , and T. Zimmermann , " Software engineering for machine learning: A case study," in ICSE-SEIP , pp. 291 -- 300 , IEEE , 2019 . S. Amershi, A. Begel, C. Bird, R. DeLine, H. Gall, E. Kamar, N. Nagappan, B. Nushi, and T. Zimmermann, "Software engineering for machine learning: A case study," in ICSE-SEIP, pp. 291--300, IEEE, 2019.

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