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Performance validation through implicit removal of infeasible paths of the behavioral description

In this paper we present a novel algorithm to identify infeasible paths in the behavioral code. The proposed approach initially partitions the behavioral code into segments. At each code segment it stores feasible paths implicitly. It also stores collections of input assignments which are derived using selected statements in the code segment. The method requires state-of-the-art data structures to store feasible paths and the required functions. Experimental results demonstrate the scalability of the proposed method.