Correctness in scientific computing (SC) is gaining increasing attention in the formal methods (FM) and programming languages (PL) community. Existing PL/FM verification techniques struggle with the complexities of realistic SC applications. Part of the problem is a lack of a common understanding between the SC and PL/FM communities of machine-verifiable correctness challenges and dimensions of correctness in SC applications. To address this gap, we call for specialized challenge problems to inform the development and evaluation of FM/PL verification techniques for correctness in SC. These specialized challenges are intended to augment existing problems studied by FM/PL researchers for general programs to ensure the needs of SC applications can be met. We propose several dimensions of correctness relevant to scientific computing, and discuss some guidelines and criteria for designing challenge problems to evaluate correctness in scientific computing.
翻译:科学计算(SC)的正确性在形式化方法(FM)和编程语言(PL)社区中正获得越来越多的关注。现有的PL/FM验证技术难以应对现实SC应用的复杂性。部分问题在于SC社区与PL/FM社区之间对机器可验证的正确性挑战以及SC应用中正确性的维度缺乏共同理解。为弥补这一差距,我们呼吁设计专门的挑战问题,以指导面向SC正确性的FM/PL验证技术的开发与评估。这些专门挑战旨在补充FM/PL研究人员为通用程序所研究的现有问题,以确保能够满足SC应用的需求。我们提出了与科学计算相关的若干正确性维度,并讨论了设计用于评估科学计算正确性的挑战问题的一些指导原则和标准。