Folded concave penalization methods have been shown to enjoy the strong oracle property for high-dimensional sparse estimation. In this talk, we will revisit the challenging fundamental issue: does the local optimum computed by a given optimization algorithm possess those nice theoretical properties? We provide a unified theory to show explicitly how to obtain the oracle solution via the local linear approximation algorithm.