Boosting operational DNN testing efficiency through conditioning

Zenan Li, Xiaoxing Ma, Chang Xu, Chun Cao, Jingwei Xu, Jian Lü

Abstract

With the increasing adoption of Deep Neural Network (DNN) models as integral parts of software systems, efficient operational testing of DNNs is much in demand to ensure these models' actual performance in field conditions. A challenge is that the testing often needs to produce precise results with a very limited budget for labeling data collected in field.

BibTeX

@inproceedings{Li-al:FSE19,
  author    = {Zenan Li and
               Xiaoxing Ma and
               Chang Xu and
               Chun Cao and
               Jingwei Xu and
               Jian L{\"{u}}},
  title     = {Boosting operational {DNN} testing efficiency through conditioning},
  booktitle = {{ESEC/SIGSOFT} {FSE}},
  pages     = {499--509},
  publisher = {{ACM}},
  year      = {2019},
}

Boosting operational DNN testing efficiency through conditioning

Abstract

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