Lazy Annotation is a method of software model checking that performs a backtracking search for a symbolic counterexample. When the search backtracks, the program is annotated with a learned fact that constrains future search. In this sense, the method is closely analogous to conflict-driven clause learning in SAT solvers. In this paper, we develop several improvements to the basic Lazy Annotation approach. The resulting algorithm is compared both conceptually and experimentally to two

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... based on similar principles but using different learning strategies: unfolding-based Bounded Model Checking and Property-Driven Reachability.