  In this paper, we develop robust estimators and tests for one-shot device
testing under proportional hazards assumption based on divergence measures.
Through a detailed Monte Carlo simulation study and a numerical example, the
developed inferential procedures are shown to be more robust than the classical
procedures, based on maximum likelihood estimators.
