We present a two-level Boolean minimization tool (BOOM) based on a new implicant generation paradigm. In contrast to all previous minimization methods, where the implicants are generated bottom-up, the proposed method uses a top-down approach. Thus instead of increasing the dimensionality of implicants by omitting literals from their terms, the dimension of a term is gradually decreased by adding new literals. Unlike most other minimization tools like ESPRESSO, BOOM doesn't use the definition of the function to be minimized as a basis for the solution, thus the original coverage influences the solution only indirectly through the number of literals used. Most minimization methods use two basic phases introduced by Quine-McCluskey, known as prime implicant (PI) generation and the covering problem solution. Some more modern methods, like ESPRESSO, combine these two phases, reducing the number of PIs to be processed. This approach is also used in BOOM, the search for new literals to...