In this paper we describe ideas used to accelerate the Searching Phase of the Berlekamp--Zassenhaus algorithm, the algorithm most widely used for computing factorizations in $\ZZ[x]$. Our ideas do not alter the theoretical worst-case complexity, but they do have a significant effect in practice: especially in those cases where the cost of the Searching Phase completely dominates the rest of the algorithm. A complete implementation of the ideas in this paper is publicly available in the library NTL~\cite{Shoup00}. We give timings of this implementation on some difficult factorization problems.