Detector-based component model abstraction for microservice-based systems
Detector-based component model abstraction for microservice-based systems
复制标题
针对基于微服务的系统的基于检测器的组件模型抽象
作者：
Evangelos Ntentos;Uwe Zdun;Konstantinos Plakidas;Patric Genfer;Sebastian Geiger;Sebastian Meixner;W. Hasselbring
软件架构的主要问题之一是避免各种复杂软件系统中的架构模型漂移和侵蚀。基于微服务的系统在这种情况下引入了新的挑战，因为它们经常在最新的迭代中使用多种技术，并且更改和发布非常频繁。可用于重建架构模型的现有解决方案无法应对这些新挑战，因为它们无法轻松应对持续演进，准确性太低，并且不能很好地支持高度多语言设置。在这项工作中，我们报告了一项研究，旨在设计一种高度准确的架构模型抽象方法，用于理解能够应对持续演进的高度多语言系统的组件架构模型。在分析相关研究结果后，我们发现了两种可能满足我们研究要求的架构模型抽象方法：机会主义方法和可重用的基于半自动检测器的方法。我们进行了实证案例研究来验证和比较这两种方法。我们的结论是这两种检测器方法都是可行的。在我们的案例研究中，如果探测器的适度重用是可能的，那么可重用方法在建立重用所需的时间和精力方面是平衡的，并且比机会主义方法产生稍微更高质量和进化稳定的解决方案。
One of the chief problems in software architecture is avoiding architecture model drift and erosion in all kinds of complex software systems. Microservice-based systems introduce new challenges in this context, as they often use a large variety of technologies in their latest iteration, and are changed and released very frequently. Existing solutions that can be used to reconstruct architecture models fall short in addressing these new challenges, as they cannot easily cope with continuous evolution, their accuracy is too low, and highly polyglot settings are not supported well. In this work, we report on a research study aiming to design a highly accurate architecture model abstraction approach for comprehending component architecture models of highly polyglot systems that can cope with continuous evolution. After analyzing the results of related studies, we found two possible architecture model abstraction approaches that meet the requirements of our study: an opportunistic, and a reusable semi-automatic detector-based approach. We have conducted an empirical case study for validation and comparison of the two approaches. We conclude that both detector approaches are feasible. In our case study, the reusable approach breaks even in terms of time and effort needed for establishing reuse, if modest reuse of detectors is possible, and is producing slightly more high quality and evolution-stable solutions than the opportunistic approach.