Explicit and implicit algorithms for binate covering problems

We survey techniques for solving binate covering problems, an optimization step often occurring in logic synthesis applications. Standard exact solutions are found with a branch-and-bound exhaustive search, made more efficient by bounding away regions of the search space. Standard approaches are said to be explicit because they work on a direct representation of the binate table, usually as a matrix. Recently, covering problems involving large tables have been attacked with implicit techniques. They are based on the representation by reduced-ordered binary decision diagrams of an encoding of the binate table. We show how table reductions, computation of a lower bound, and of a branching column can be performed on the table so represented. We report experiments for two different applications that demonstrate that implicit techniques handle instances beyond the reach of explicit techniques. Various aspects of our original research are presented for the first time, together with a selection of the most important old and new results scattered in many sources