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A neural network algorithm for hardware-software verification

机译:一种用于软硬件验证的神经网络算法

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摘要

Formal verification is the task of proving that a property holds for a model of a design. This paper examines the idea of a Neural Network-based algorithm used to find the set of states that makes a specification valid. The paper addresses a singular approach for those doing theoretical research for the verification of soft programs, and, for hardware designers. The approach of the application of the Artificial Neural Network is not new, but it becomes interesting if one can improve the truth-building efficiency by using some known artifices. Topics described include Integer Linear Programming, Propositional Logic, Model Checking, Satisfiability problems (SAT) and Artificial Neural Networks (ANN).
机译:形式验证是证明属性对设计模型有效的任务。本文研究了一种基于神经网络的算法的思想,该算法用于查找使规范有效的状态集。本文针对那些进行理论研究以验证软件程序以及硬件设计人员的方法,提出了一种奇异的方法。人工神经网络的应用方法并不新颖,但是如果人们可以通过使用一些已知的技巧来提高真相建立效率,就会变得很有趣。描述的主题包括整数线性规划,命题逻辑,模型检查,可满足性问题(SAT)和人工神经网络(ANN)。

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