Hybrid Theorem Proving as a Lightweight Method for Verifying Numerical Software

Alper Altuntas, J. Baugh
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引用次数: 2

Abstract

Large-scale numerical software requires substantial computer resources that complicate testing and debugging. A single run of a climate model may require many millions of core-hours and terabytes of disk space, making trial-and-error experiments burdensome and time consuming. In this study, we apply hybrid theorem proving from the field of cyber-physical systems to problems in scientific computation, and show how to verify the correctness of discrete updates that appear in the simulation of continuous physical systems. By viewing numerical software as a hybrid system that combines discrete and continuous behavior, test coverage and confidence in findings can be increased. We describe abstraction approaches for modeling numerical software and demonstrate the applicability of the approach in a case study that reproduces undesirable behavior encountered in a parameterization scheme, called the K-profile parameterization, widely used in ocean components of large-scale climate models. We then identify and model a fix in the configuration of the scheme, and verify that the undesired behavior is eliminated for all possible execution sequences. We conclude that hybrid theorem proving is an effective and efficient approach that can be used to verify and reason about properties of large-scale numerical software.
混合定理证明作为一种轻量级的数值软件验证方法
大型数值软件需要大量的计算机资源,使测试和调试复杂化。一个气候模型的单次运行可能需要数百万核小时和tb的磁盘空间,这使得反复试验变得繁琐而耗时。在本研究中,我们将网络物理系统领域的混合定理证明应用于科学计算问题,并展示了如何验证连续物理系统仿真中出现的离散更新的正确性。通过将数值软件视为结合离散和连续行为的混合系统,可以增加测试覆盖率和对结果的信心。我们描述了模拟数值软件的抽象方法,并在一个案例研究中证明了该方法的适用性,该案例研究再现了在参数化方案中遇到的不良行为,称为k -剖面参数化,广泛用于大尺度气候模式的海洋组分。然后,我们在方案的配置中识别和建模修复,并验证所有可能的执行序列都消除了不希望的行为。混合定理证明是一种有效的方法,可用于验证和推理大型数值软件的性质。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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