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Automated Code-Smell Detection in Microservices Through Static Analysis: A Case Study

机译:通过静态分析自动化的码味在微服务中检测:一个案例研究

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摘要

Microservice Architecture (MSA) is becoming the predominant direction of new cloud-based applications. There are many advantages to using microservices, but also downsides to using a more complex architecture than a typical monolithic enterprise application. Beyond the normal poor coding practices and code smells of a typical application, microservice-specific code smells are difficult to discover within a distributed application setup. There are many static code analysis tools for monolithic applications, but tools to offer code-smell detection for microservice-based applications are lacking. This paper proposes a new approach to detect code smells in distributed applications based on microservices. We develop an MSANose tool to detect up to eleven different microservice specific code smells and share it as open-source. We demonstrate our tool through a case study on two robust benchmark microservice applications and verify its accuracy. Our results show that it is possible to detect code smells within microservice applications using bytecode and/or source code analysis throughout the development process or even before its deployment to production.
机译:微服务架构(MSA)正在成为新的基于云的应用程序的主要方向。使用微服务有许多优点,还可以使用比典型的单片企业应用更复杂的体系结构。除了典型应用程序的正常差的编码实践和代码味道之外,在分布式应用程序设置中难以发现微服务特定的代码气味。缺乏许多用于单片应用的静态代码分析工具,但工具提供了为基于微服务的应用程序提供码味检测的工具。本文提出了一种基于微服务的分布式应用中检测代码气味的新方法。我们开发了一个MSALESE工具,可以检测到11个不同的微服务特定代码气味并将其分享为开源。我们通过对两个强大的基准微服务应用程序进行案例研究来展示我们的工具,并验证其准确性。我们的结果表明,可以在整个开发过程中使用字节码和/或源代码分析来检测微服务和/或源代码分析中的MicroService应用程序中的代码闻。

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