Visible to the public Mining Software Repositories for Predictive Modelling of Defects in SDN Controller

TitleMining Software Repositories for Predictive Modelling of Defects in SDN Controller
Publication TypeConference Paper
Year of Publication2019
AuthorsVizarreta, Petra, Sakic, Ermin, Kellerer, Wolfgang, Machuca, Carmen Mas
Conference Name2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)
ISBN Number978-3-903176-15-7
Keywordsbug characteristics, bug manifestation, bug removal rates, bug repository, Computer bugs, computer network management, Configuration Management, control systems, data mining, Git version control system, Metrics, mining software repositories, network operating system, open source SDN controller platform, OpenDaylight architecture, predictive modelling, predictive security metrics, production grade SDN controller, program debugging, Protocols, pubcrawl, public domain software, reliability, security, Software, software defect metrics, software defined networking, software defined networking control plane, software development management, software metrics, software release management, Stochastic processes

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.

Citation Keyvizarreta_mining_2019