微处理器功能验证的定向逻辑测试

Michael Katelman, J. Meseguer, Santiago Escobar
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引用次数: 8

摘要

微处理器开发周期的长度在很大程度上取决于功能验证,而当代实践主要依赖于基于约束的随机刺激生成来驱动基于仿真的方法。然而,正式方法尤其得到了更广泛的采用,并被视为具有弥补当前技术留下的巨大差距的潜力。许多差距仍然存在。本文提出了一种基于纯逻辑技术(即形式化方法)的刺激生成新方法——定向逻辑测试。据我们所知,我们的方法代表了刺激产生问题的第一个端到端数学形式化。因此,本文的一个主要贡献是定义了一类逻辑命题,这些命题与实际的微处理器实现、汇编程序刺激和覆盖目标有关。在重写逻辑中给出了这些命题,并利用重写语义的思想在一个共同的逻辑框架内自动形式化了微处理器实现和汇编程序。为了解决这些问题,我们演示了如何将窄化和用户定义的窄化策略用作可扩展的逻辑框架。此外,我们还描述了两类可用于许多微处理器和常见覆盖目标的有效策略。最后,我们描述了一个原型工具的实现,并提供了经验数据来证明我们的方法的可行性。由于重写逻辑中的缩小和用户定义的缩小策略还没有工具支持,我们的原型工具使用标准的重写和用户定义的重写策略来模拟缩小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Directed-Logical Testing for Functional Verification of Microprocessors
The length of the microprocessor development cycle is largely determined by functional verification, where contemporary practice relies primarily on constraint-based random stimulus generation to drive a simulation-based methodology. However, formal methods are, in particular, gaining wider adoption and are seen as having potential to bridge large gaps left by current techniques. And many gaps still remain. In this paper we propose directed- logical testing: a new method of stimulus generation based on purely logical techniques (i.e. formal methods). As far as we know, our methodology represents the first end-to-end mathematical formalization of the stimulus generation problem. Therefore, a major contribution of this paper is the definition of a class of logical propositions that relate the actual microprocessor implementation, the assembly program stimulus, and a coverage goal. These propositions are given in rewriting logic, and use the idea of rewriting semantics to automatically formalize within a common logical framework the microprocessor implementation and assembly programs. To solve these propositions, we demonstrate how narrowing and user-defined narrowing strategies can be used as a scalable logical framework. In addition, we describe two classes of effective strategies that can be used for many microprocessors and common coverage goals. Finally, we describe a prototype tool implementation and present empirical data to demonstrate the feasibility of our methodology. Since narrowing and user-defined narrowing strategies within rewriting logic do not yet have tool support, our prototype tool uses standard rewriting and user-defined rewriting strategies to simulate narrowing.
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