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This article has three main contributions to our understanding of minimax search: First, a new formulation for Stockman's SSS^∗ algorithm, based on Alpha-Beta, is presented. It solves all the perceived drawbacks of SSS^∗, finally transforming it into a practical algorithm. In effect, we show that SSS^∗ = Alpha-Beta + transposition tables. The crucial step is the realization that transposition tables contain so-called solution trees, structures that are used in best-first search algorithms like SSS^∗. Having created a practical version, we present performance measurements with tournament game-playing programs for three different minimax games, yielding results that contradict a number of publications. Second, based on the insights gained in our attempts at understanding SSS^∗, we present a framework that facilitates the construction of several best-first fixed-depth game-tree search algorithms, known and new. The …