Heuristic search is a core area of Artificial Intelligence with applications to planning, scheduling and game playing. Real-time heuristic search applies to search problems where plan execution needs to start before a complete solution can be computed. Since the inception of real-time heuristic search in the early 1990s a great number of algorithms have been proposed and evaluated. In this paper we break them down into building blocks and conduct a search in the space of such building blocks. Even simple tabulated and iterative searches find new real-time heuristic search algorithms outperforming manually crafted contemporary algorithms.