An empirical evaluation of flow based programming in the machine learning deployment context-Reference-Cited by-同舟云学术

An empirical evaluation of flow based programming in the machine learning deployment context

Published:2022-05-16 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 1st International Conference on AI Engineering: Software Engineering for AI
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Author:

Paleyes Andrei¹,Cabrera Christian¹,Lawrence Neil D.¹

Affiliation:

1. University of Cambridge, United Kingdom

Funder

Alan Turing Institute

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3522664.3528601

Reference53 articles.

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2. H Bergius . 2015. NoFlo-flow-based programming for Javascript. URL: http://noflojs.org ( 2015 ). H Bergius. 2015. NoFlo-flow-based programming for Javascript. URL: http://noflojs.org (2015).

3. Tom Borchert . 2020 . Milan: An Evolution of Data-Oriented Programming. Available at https://tborchertblog.wordpress.com/2020/02/13/28/. Tom Borchert. 2020. Milan: An Evolution of Data-Oriented Programming. Available at https://tborchertblog.wordpress.com/2020/02/13/28/.

4. Christian Cabrera , Fan Li , Vivek Nallur , Andrei Palade , MA Razzaque , Gary White , and Siobhan Clarke . 2017 . Implementing heterogeneous, autonomous, and resilient services in IoT: An experience report. In A World of Wireless , Mobile and Multimedia Networks (WoWMoM), 2017 IEEE 18th International Symposium on. IEEE, 1--6. Christian Cabrera, Fan Li, Vivek Nallur, Andrei Palade, MA Razzaque, Gary White, and Siobhan Clarke. 2017. Implementing heterogeneous, autonomous, and resilient services in IoT: An experience report. In A World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2017 IEEE 18th International Symposium on. IEEE, 1--6.

5. Cognitive complexity

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