用技术滞后来表征过时:一项探索性研究

Jesus M. Gonzalez-Barahona
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引用次数: 4

摘要

背景:如今,许多应用程序都是重用大量组件构建的,这些组件是从npm (JavaScript)或PyPi (Python)等软件集合中检索的。这些组件构建在相应的上游存储库中,在那里开发它们。当应用程序部署在生产环境中时,这种重用体系结构会对其过时程度产生一些限制。目标:了解如何计算应用程序及其所依赖的组件的过时性,以便在度量标准的帮助下测量和评估不同的情况。基于这种理解,我们还希望生成一个模型来描述生态系统(可重用组件的集合)。方法:使用技术滞后框架来分析从上游存储库到组件集合,再到应用程序构建和后期部署的流程。使用这个框架,分析每个阶段的版本可用性延迟,以及限制部署的过时应用程序的限制。结果:我们定义了一个模型,该模型使我们能够更好地理解影响由组件存储库中的可重用组件生成的应用程序的过时性的因素。该模型允许我们找到定义度量过时性的度量标准的因素,并探索影响应用程序中组件过时性的因素。我们提出其中一些因素作为描述生态系统或组件集合的基础,以及它们对使用它们构建的应用程序的过时性的影响。结论:技术滞后是研究从上游开发到部署的版本传播滞后的合适框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Characterizing outdateness with technical lag: an exploratory study
Background: Nowadays, many applications are built reusing a large number of components, retrieved from software collections such as npm (JavaScript) or PyPi (Python). Those components are built in their corresponding upstream repositories, where they are being developed. This architecture of reusing causes some constraints on how much outdated is an application when it is deployed in production environments. Goal: To understand how outdateness of applications, and the components on which they depend, can be computed, so that different situations can be measured and assessed with the help of metrics. Based on this understanding, we also want to produce a model to characterize ecosystems (collections of reusable components). Method: Use the technical lag framework to analyze the flows from upstream repositories, to collection of components, to application building and later deployment. Using this framework, analyze lag in version availability in each of these stages, and constraints that set limits on how much outdated can be deployed applications. Results: We define a model which allows us to better understand the factors that influence outdateness of an application produced with reusable components from repositories of components. The model allows us to find the factors for defining metrics for measuring outdateness, and to explore the factors that influence outdateness for components in applications. We propose some of those factors as the basis to characterize ecosystems or collections of components with respect to their impact on the outdateness of applications built with them. Conclusions: Technical lag is an appropriate framework for studying lags in version propagation from upstream development to deployment.
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