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Mining Software Repositories for Predictive Modelling of Defects in SDN Controller

机译:挖掘软件存储库,以在SDN控制器中对缺陷进行预测建模

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In Software Defined Networking (SDN) control plane of forwarding devices is concentrated in the SDN controller, which assumes the role of a network operating system. Big share of today's commercial SDN controllers are based on OpenDaylight, an open source SDN controller platform, whose bug repository is publicly available. In this article we provide a first insight into 8k+ bugs reported in the period over five years between March 2013 and September 2018. We first present the functional components in OpenDaylight architecture, localize the most vulnerable modules and measure their contribution to the total bug content. We provide high fidelity models that can accurately reproduce the stochastic behaviour of bug manifestation and bug removal rates, and discuss how these can be used to optimize the planning of the test effort, and to improve the software release management. Finally, we study the correlation between the code internals, derived from the Git version control system, and software defect metrics, derived from Jira issue tracker. To the best of our knowledge, this is the first study to provide a comprehensive analysis of bug characteristics in a production grade SDN controller.
机译:在软件定义网络(SDN)中,转发设备的控制平面集中在SDN控制器中,该控制器承担网络操作系统的角色。当今的商用SDN控制器中,有很大一部分都基于OpenDaylight,这是一个开源SDN控制器平台,其错误存储库是公开可用的。在本文中,我们提供了对2013年3月至2018年9月这五年内报告的8k + bug的初步了解。我们首先介绍OpenDaylight架构中的功能组件,对最易受攻击的模块进行本地化,并评估它们对bug总量的贡献。我们提供了高保真度模型,可以准确地再现错误表现和错误清除率的随机行为,并讨论如何使用这些模型来优化测试工作的计划并改善软件发布管理。最后,我们研究了从Git版本控制系统派生的代码内部与从Jira问题跟踪器派生的软件缺陷度量之间的相关性。据我们所知,这是第一项对生产级SDN控制器中的错误特征进行全面分析的研究。

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