Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Existing dier ence logic (DL) solvers can be broadly classied as eager or lazy, each with its own merits and de-merits.  propose a novel dier ence logic solver SDSAT that combines the strengths of both these approaches and provides a robust performance over a wide set of benchmarks. The solver SDSAT works in two phases: allocation and solve. In the allocation phase, it allocates non-uniform adequate ranges for variables appearing in dierence predicates. This phase is similar to previous small domain encoding approaches, but uses a novel algorithm Nu-SMOD with 1-2 orders of magnitude improvement in performance and smaller ranges for variables. Furthermore, the dier ence logic formula is not transformed into an equi-satisable Boolean formula in a single step, but rather done lazily in the following phase. In the solve phase, SDSAT uses a lazy renemen t approach to search for a satisfying model within the allocated ranges. Thus, any partially DL-theory consistent model can be discarded if it cannot be satised within the allocated ranges. Note the crucial dierence: in eager approaches, such a partially consistent model is not allod in the rst place, while in lazy approaches such a model is never discarded. Moreover,  dynamically rene the allocated ranges and search for a feasible solution within the updated ranges. This combined approach benets from both the smaller search space (as in eager approaches) and also from the theory-specic graph-based algorithms (characteristic of lazy approaches). Experimental results show that our method is robust and always better than or comparable to state-of-the art solvers using similar eager or lazy techniques.
['Malay K. Ganai', 'Muralidhar Talupur', 'Aarti Gupta']
I am writing a research paper on a idea SDSAT: Tight Integration of Small Domain Encoding and Lazy Approaches in Solving Difference Logic
[{"from": "human", "value": "I am writing a research paper on a idea SDSAT: Tight Integration of Small Domain Encoding and Lazy Approaches in Solving Difference Logic"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Existing dier ence logic (DL) solvers can be broadly classied as eager or lazy, each with its own merits and de-merits.  propose a novel dier ence logic solver SDSAT that combines the strengths of both these approaches and provides a robust performance over a wide set of benchmarks. The solver SDSAT works in two phases: allocation and solve. In the allocation phase, it allocates non-uniform adequate ranges for variables appearing in dierence predicates. This phase is similar to previous small domain encoding approaches, but uses a novel algorithm Nu-SMOD with 1-2 orders of magnitude improvement in performance and smaller ranges for variables. Furthermore, the dier ence logic formula is not transformed into an equi-satisable Boolean formula in a single step, but rather done lazily in the following phase. In the solve phase, SDSAT uses a lazy renemen t approach to search for a satisfying model within the allocated ranges. Thus, any partially DL-theory consistent model can be discarded if it cannot be satised within the allocated ranges. Note the crucial dierence: in eager approaches, such a partially consistent model is not allod in the rst place, while in lazy approaches such a model is never discarded. Moreover,  dynamically rene the allocated ranges and search for a feasible solution within the updated ranges. This combined approach benets from both the smaller search space (as in eager approaches) and also from the theory-specic graph-based algorithms (characteristic of lazy approaches). Experimental results show that our method is robust and always better than or comparable to state-of-the art solvers using similar eager or lazy techniques."}]