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Application of Formal Word-Level Analysis toConstrained Random Simulation Tool Paper

机译:形式词级分析在约束随机仿真工具中的应用

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Constrained random simulation is supported by constraint solvers integrated within simulators. These constraint solvers need to be fast and memory efficient to maintain simulation performance. Binary Decision Diagrams (BDDs) have been successfully applied to represent constraints in this context. However, BDDs are vulnerable to size explosions depending on the constraints they are representing and the number of Boolean variables appearing in them. In this paper, we present a word-level analysis tool DomRed to reduce the number of Boolean variables required to represent constraints by reducing the domain of constraint variables. DomRed employs static analysis techniques to obtain these reductions. We present experimental results to illustrate the impact of this tool.
机译:集成在模拟器中的约束求解器支持约束随机仿真。这些约束求解器需要快速且内存有效,以保持仿真性能。在这种情况下,二进制决策图(BDD)已成功应用于表示约束。但是,BDD容易受到大小爆炸的影响,具体取决于它们所代表的约束条件和其中出现的布尔变量的数量。在本文中,我们提出了一种词级分析工具DomRed,它通过减少约束变量的域来减少表示约束所需的布尔变量的数量。 DomRed采用静态分析技术来获得这些减少量。我们提供实验结果来说明此工具的影响。

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