%0 Generic %1 vizarreta2019mining %A Vizarreta, Petra %A Sakic, Ermin %A Kellerer, Wolfgang %A Mas Machuca, Carmen %B IFIP/IEEE International Symposium on Integrated Network Management 2019 %D 2019 %K sendate sendate-planets %T Mining Software Repositories for Predictive Modelling of Defects in SDN Controller %U https://mediatum.ub.tum.de/node?id=1469844 %X 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.

@conference{vizarreta2019mining, abstract = {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 \textit{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 \textit{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.}, added-at = {2019-01-28T16:35:43.000+0100}, author = {Vizarreta, Petra and Sakic, Ermin and Kellerer, Wolfgang and Mas Machuca, Carmen}, biburl = {https://www.bibsonomy.org/bibtex/2de854ce294f3d225dd0fe88f3d8d5d30/lkn}, booktitle = {IFIP/IEEE International Symposium on Integrated Network Management 2019}, interhash = {710aa51b778030666e71c934d231a4cf}, intrahash = {de854ce294f3d225dd0fe88f3d8d5d30}, keywords = {sendate sendate-planets}, timestamp = {2019-01-28T16:35:43.000+0100}, title = {Mining Software Repositories for Predictive Modelling of Defects in SDN Controller }, url = {https://mediatum.ub.tum.de/node?id=1469844}, year = 2019 }