在Apache Spark上执行经过认证的模型转换

Jolan Philippe, M. Tisi, Hélène Coullon, G. Sunyé
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引用次数: 1

摘要

模型转换语言的形式化推理允许用户根据契约证明模型转换。CoqTL在Coq交互定理证明器中包含了转换引擎的规范。可以从该规范中自动提取可执行引擎。转换契约由用户根据CoqTL规范证明,并保证在提取的CoqTL实现上运行的转换保持不变。CoqTL中转换引擎规范的设计旨在简化认证步骤,但这一需求损害了提取引擎的执行性能。在本文中,我们的目标是提供CoqTL规范的可伸缩分布式实现。为了实现这一目标,我们分两个步骤进行。首先,我们引入了一个改进的CoqTL规范,它增加了引擎的并行化。我们给出了一个与标准CoqTL等价的机械化证明。其次,我们在Spark之上开发了一个精细化规范的原型实现。最后,通过评估一个简单的案例研究的性能,我们评估我们的解决方案可以达到的加速。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Executing certified model transformations on Apache Spark
Formal reasoning on model transformation languages allows users to certify model transformations against contracts. CoqTL includes a specification of a transformation engine in the Coq interactive theorem prover. An executable engine can be automatically extracted from this specification. Transformation contracts are proved by the user against the CoqTL specification and guaranteed to hold on the transformation running on the extracted implementation of CoqTL. The design of the transformation engine specification in CoqTL aims at easing the certification step, but this requirement harms the execution performance of the extracted engine. In this paper, we aim at providing a scalable distributed implementation of the CoqTL specification. To achieve this objective we proceed in two steps. First, we introduce a refined specification of CoqTL that increases the engine parallelization. We present a mechanized proof of the equivalence with standard CoqTL. Second, we develop a prototype implementation of the refined specification on top of Spark. Finally, by evaluating the performance of a simple case study, we assess the speedup our solution can reach.
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