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The evolved, core helium burning, extreme horizontal branch stars (also known as hot B subdwarfs) host several classes of pulsators showing either p- or g-modes, or both. They offer particularly favorable conditions for probing with asteroseismology their internal structure, thus constituting arguably the most interesting seismic window for this intermediate stage of stellar evolution. G-modes in particular have the power to probe deep inside these stars, down to the convective He-burning core boundary where uncertain physics (convection, overshooting, semi-convection) is at work. Space data recently obtained with CoRoT and Kepler are offering us the possibility to probe these regions in detail and possibly shed new light on how these processes shape the core structure. In this short paper, we present the most recent advances that have taken place in this field and we provide hints of the foreseen future achievements of hot subdwarf asteroseismology.

Asteroseismic modeling of subdwarf B (sdB) stars provides measurements of their fundamental parameters with a very good precision; in particular, the masses and radii determined from asteroseismology are found to typically reach a precision of 1% containing various uncertainties associated with their inner structure and the underlying microphysics (composition and transition zones profiles, nuclear reaction rates, etc.). Therefore, the question of the accuracy of the stellar parameters derived by asteroseismology is legitimate. We present here the seismic modeling of the pulsating sdB star in the eclipsing binary PG 1336–018, for which the mass and the radius are independently and precisely known from the modeling of the reflection/irradiation effect and the eclipses observed in the light curve. This allows us to quantitatively evaluate the reliability of the seismic method and test the impact of uncertainties in our stellar models on the derived parameters. We conclude that the sdB star parameters inferred from asteroseismology are precise, accurate, and robust against model uncertainties.