The low cost and rapid provisioning capabilities have made open-source cloud a desirable platform to launch industrial applications. However, as open-source cloud moves towards maturity, it still suffers from quality issues like code smells. Although, a great emphasis has been provided on the economic benefits of deploying open-source cloud, low importance has been provided to improve the quality of the source code of the cloud itself to ensure its maintainability in the industrial scenario. Code refactoring has been associated with improving the maintenance and understanding of software code by removing code smells. However, analyzing what smells are more prevalent in cloud environment and designing a tool to define and detect those smells require further attention. In this paper, we propose a model called CloudScent which is an open source mechanism to detect smells in open-source cloud. We test our experiments in a real-life cloud environment using OpenStack. Results show that CloudScent is capable of accurately detecting 8 code smells in cloud. This will permit cloud service providers with advanced knowledge about the smells prevalent in open-source cloud platform, thus allowing for timely code refactoring and improving code quality of the cloud platforms.

翻译：开源云端因其低成本和快速部署能力，已成为部署工业应用的理想平台。然而，随着开源云端走向成熟，它仍然面临着诸如代码异味等质量问题。尽管人们高度重视部署开源云端的经济效益，但对提高云端自身源代码质量以保障其在工业场景中的可维护性却重视不足。代码重构通过消除代码异味，已被认为能够改善软件代码的维护性和理解性。然而，分析云端环境中哪些异味更为普遍，并设计工具来定义和检测这些异味，仍需进一步关注。本文提出一种名为CloudScent的模型，这是一种开源机制，用于检测开源云端中的异味。我们利用OpenStack在真实云端环境中进行实验。结果表明，CloudScent能够准确检测云端中的8种代码异味。这将使云服务提供商能够深入了解开源云平台上普遍存在的异味，从而及时进行代码重构，提升云平台的代码质量。