A Static Model-Based Engine for Model-Based Reasoning

Most systems for model–based reasoning record justifications during the search for solutions. In the popular ATMS systems this can lead to an explosion of recorded information when solving complicated problems. We propose an engine for model– based reasoning which works directly on logical models, uses static precompiled information on the structure of the underlying theory and does no further recording during search. This engine (DRUM– II) solves large complicated problems with attractive time and space complexity. To demonstrate the efficiency of the engine we give a new characterization of a popular benchmark suite, solve it with our engine and compare the performance to previous results.