We present methodology to achieve the automated variability classification of stars based on photometric time series. Our work is done in the framework of the COROT space mission to be launched in 2006, but will also be applicable to data of the future Gaia satellite. We developed routines that are able to handle a large amount of light curves in a short computation time. The current methods are based on Multivariate and Bayesian statistics. A selection of HIPPARCOS light curves is used as a test-dataset to evaluate both methods. We indicate our future plans for improvements of the methods.

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Astrophysics of Variable Stars