This paper introduces GRASP (Generic Search Algorithm for the Satisfiability Problem), an integrated framework for SAT that combines several search-pruning techniques and facilitates the identification of additional ones. GRASP is based on the idea of augmenting basic backtracking search with a powerful conflict analysis procedure. This procedure allows GRASP to backtrack non-chronologically, pruning large portions of the search space and recognizing and preempting similar conflicts. The conflict analysis also helps identify necessary assignments for a solution. Experimental results on a wide range of benchmarks, including those from test pattern generation, show that GRASP outperforms state-of-the-art SAT algorithms in many cases. The paper discusses the implementation details of GRASP, its performance on different benchmarks, and future research directions, emphasizing the potential of conflict analysis in improving SAT solving efficiency.This paper introduces GRASP (Generic Search Algorithm for the Satisfiability Problem), an integrated framework for SAT that combines several search-pruning techniques and facilitates the identification of additional ones. GRASP is based on the idea of augmenting basic backtracking search with a powerful conflict analysis procedure. This procedure allows GRASP to backtrack non-chronologically, pruning large portions of the search space and recognizing and preempting similar conflicts. The conflict analysis also helps identify necessary assignments for a solution. Experimental results on a wide range of benchmarks, including those from test pattern generation, show that GRASP outperforms state-of-the-art SAT algorithms in many cases. The paper discusses the implementation details of GRASP, its performance on different benchmarks, and future research directions, emphasizing the potential of conflict analysis in improving SAT solving efficiency.