Code smells are poor implementation choices applied by developers during software evolution that often lead to critical flaws or failure. Much in the same way, community smells reflect the presence of organizational and socio-technical issues within a software community that may lead to additional project costs. Recent empirical studies provide evidence that community smells are often—if not always—connected to circumstances such as code smells. In this paper we look deeper into this connection by conducting a mixed-methods empirical study of 117 releases from 9 open-source systems. The qualitative and quantitative sides of our mixed-methods study were run in parallel and assume a mutually-confirmative connotation. On the one hand, we survey 162 developers of the 9 considered systems to investigate whether developers perceive relationship between community smells and the code smells found in those projects. On the other hand, we perform a fine-grained analysis into the 117 releases of our dataset to measure the extent to which community smells impact code smell intensity (i.e., criticality). We then propose a code smell intensity prediction model that relies on both technical and community-related aspects. The results of both sides of our mixed-methods study lead to one conclusion: community-related factors contribute to the intensity of code smells. This conclusion supports the joint use of community and code smells detection as a mechanism for the joint management of technical and social problems around software development communities.

中文翻译：

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超越技术方面：社区气味如何影响代码气味的强度？

代码异味是开发人员在软件演化过程中应用的糟糕实现选择，通常会导致严重缺陷或失败。以同样的方式，社区气味反映了软件社区内可能导致额外项目成本的组织和社会技术问题的存在。最近的实证研究提供的证据表明，社区气味通常（如果不总是）与代码气味等环境有关。在本文中，我们通过对 9 个开源系统的 117 个版本进行混合方法实证研究来更深入地研究这种联系。我们的混合方法研究的定性和定量方面是并行进行的，并具有相互确认的内涵。一方面，我们调查了 9 个考虑系统的 162 名开发人员，以调查开发人员是否感知社区气味与这些项目中发现的代码气味之间的关系。另一方面，我们对我们数据集的 117 个版本进行了细粒度分析，以衡量社区气味对代码气味强度（即关键性）的影响程度。然后，我们提出了一个依赖于技术和社区相关方面的代码气味强度预测模型。我们的混合方法研究双方的结果得出一个结论：与社区相关的因素会导致代码异味的强度。该结论支持共同使用社区和代码异味检测作为围绕软件开发社区的技术和社会问题的联合管理机制。