Coq中基于记录数据类型的形式化内存模型可扩展性问题的解决

Zheng Yang, Hang Lei, Weizhong Qian, Zehui Yan, Weiru Zeng
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引用次数: 0

摘要

形式化内存模型是程序验证工具开发中最关键的组成部分之一。从理论上讲,基于记录数据类型的形式化存储模型是一种直观、高效的形式化方案。然而,由于可扩展性问题,基于记录数据类型的形式化内存模型在Coq中的实际应用受到了限制。目前的工作通过在Coq中定义一个具有模块化多态性的新的多级表框架来解决这个问题。首先,我们提出了形式化内存模型的多态元规范和相应的操作。其次,通过模块的多态实例化和递归嵌套相结合,模拟了线性递归和尾递归原理。在此基础上,构造了一种新的基于记录类型的具有多级表结构的形式化存储模型的抽象规范和相应的存储操作。最后,我们定义了一个逻辑-物理内存转换率来量化可扩展性的优化,并给出了一系列基于该比率的实验来证明优化后的Coq框架与传统定义相比可扩展性的提高。
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A Resolution for Scalability Problem of Record Datatype Based Formal Memory Models in Coq
The formal memory model is one of the most critical components for program verification tools development. Theoretically, the record datatype based formal memory model is a type of intuitive and efficient formalization scheme. However, practical applications of record datatype based formal memory models in Coq are limited because of their scalability problem. Present work addresses this issue by defining a new multi-level table framework with modular polymorphism in Coq. First, we present polymorphic meta specifications of formal memory model and corresponding operations. Second, through the combination of polymorphic instantiation and recursive nesting of modules, we simulate the linear and tail recursion principles. With these principles, a new record type based abstract specifications of formal memory model with multi-level table structure and corresponding memory operations are constructed. Finally, we define a logic-physical memory conversion ratio to quantify the optimization of scalability, and we present a series experiments based on the ratio to certify the improvement of scalability of the optimized framework in Coq compared with conventional definitions.
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