Paper  abstract   bibtex   

@INPROCEEDINGS{Washizaki22-PLoP-SEP4MLAPart4,
   AUTHOR       = {Hironori Washizaki and Foutse Khomh and 
      Yann-Ga�l Gu�h�neuc},
   BOOKTITLE    = {Proceedings of the 29<sup>th</sup> Conference on Pattern Languages of Programs (PLoP)},
   TITLE        = {Software Engineering Patterns for Machine Learning 
      Applications (SEP4MLA) - Part 4 - ML Gateway Routing Architecture},
   YEAR         = {2022},
   OPTADDRESS   = {},
   OPTCROSSREF  = {},
   EDITOR       = {Mary Lynn Manns and Eduardo Guerra},
   MONTH        = {October},
   NOTE         = {10 pages.},
   OPTNUMBER    = {},
   OPTORGANIZATION = {},
   PAGES        = {1--10},
   PUBLISHER    = {ACM Press},
   OPTSERIES    = {},
   OPTVOLUME    = {},
   KEYWORDS     = {Topic: <b>Design patterns</b>, Venue: <c>PLoP</c>},
   URL          = {http://www.ptidej.net/publications/documents/PLoP22.doc.pdf},
   ABSTRACT     = {Machine learning (ML) researchers study the best 
      practices to develop and support ML-based applications to ensure 
      quality and determine the constraints applied to their application 
      pipelines. Such practices are often formalized as software patterns. 
      We discovered software-engineering design patterns for 
      machine-learning applications by thoroughly searching the available 
      literature on the subject. Among the ML patterns found, we describe 
      in this paper one ML topology pattern, ``ML Gateway Routing 
      Architecture'', in the standard pattern format so that practitioners 
      can (re)use it in their contexts and benefits. The pattern addresses 
      the problem of tight coupling among ML-implemented and non-ML 
      business logic as well as the front-end client by installing a 
      gateway that routes requests.}
}