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Composing Message Translators and Inferring Their Data Types Using Tree Automata

机译:使用树自动机来组成消息翻译器并推断其数据类型

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Modern distributed systems and Systems of Systems (SoS) are built as a composition of existing components and services. As a result, systems communicate (either internally, locally or over networks) using protocol stacks of ever-increasing complexity whose messages need to be translated (i.e., interpreted, generated, analyzed and transformed) by third-party systems such as services dedicated to security or interoperability. We observe that current approaches in software engineering are unable to provide an efficient solution towards reusing message translators associated with the message formats composed in protocol stacks. Instead, developers must write ad hoc "glue-code" whenever composing two or more message translators. In addition, the data structures of the output must be integrated/harmonized with the target system. In this paper we propose a solution to the above that enables the composition of message translators according to a high-level user-provided query. While the composition scheme we propose is simple, the inference of the resulting data structures is a problem that has not been solved up to now. This leads us to contribute with a novel data type inference mechanism, which generates a data-schema using tree automata, based on the aforementioned user query.
机译:现代分布式系统和系统系统(SOS)作为现有组件和服务的构成构成。结果,系统使用协议堆栈(内部,本地,本地,本地,本地或网络)进行通信,其消息需要由诸如专用于的服务的第三方系统(即,解释,生成,分析和转换)。安全性或互操作性。我们观察到,软件工程中的当前方法无法向重用与协议栈中组合的消息格式相关联的消息转换器提供有效的解决方案。相反,开发人员必须在编写两个或多个消息翻译时写入Ad Hoc“粘合代码”。此外,输出的数据结构必须与目标系统集成/统一。在本文中,我们提出了一种解决方案,该解决方案能够根据高级用户提供的查询来实现消息翻译器的组成。虽然我们提出的组合方案很简单,所得到的数据结构的推断是现在尚未解决的问题。这导致我们用新颖的数据类型推理机制贡献,该机制基于上述用户查询使用树自动机生成数据模式。

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