On Extending the Automatic Test Markup Language (ATML) for Machine Learning

arXiv:2404.03769v1 Announce Type: cross
Abstract: This paper addresses the urgent need for messaging standards in the operational test and evaluation (T&E) of machine learning (ML) applications, particularly in edge ML applications embedded in systems like robots, satellites, and unmanned vehicles. It examines the suitability of the IEEE Standard 1671 (IEEE Std 1671), known as the Automatic Test Markup Language (ATML), an XML-based standard originally developed for electronic systems, for ML application testing. The paper explores extending IEEE Std 1671 to …

abstract applications arxiv cs.lg cs.se cs.sy edge eess.sy embedded evaluation ieee language machine machine learning markup language messaging ml applications paper robots satellites standard standards systems test type vehicles