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Continuous data-driven software engineering – towards a research agenda

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Show simple item record Gerostathopoulos, Ilias Konersmann, Marco Krusche, Stephan Mattos, David I. Bosch, Jan Bures, Tomas Fitzgerald, Brian Goedicke, Michael Muccini, Henry Olsson, Helena H. Brand, Thomas Chatley, Robert Diamantopoulos, Nikolaos Friedman, Arik Jiménez, Miguel Johanssen, Jan Ole Manggala, Putra Koseki, Masumi Melegati, Jorge Munaiah, Nuthan Tamura, Gabriel Theodorou, Vasileios Wong, Jeffrey Figalist, Iris 2020-01-21T20:12:11Z 2020-01-21T20:12:11Z 2019
dc.description peer-reviewed en_US
dc.description.abstract The rapid pace with which software needs to be built, together with the increasing need to evaluate changes for end users both quantitatively and qualitatively calls for novel software engineering approaches that focus on short release cycles, continuous deployment and delivery, experiment-driven feature development, feedback from users, and rapid tool-assisted feedback to developers. To realize these approaches there is a need for research and innovation with respect to automation and tooling, and furthermore for research into the organizational changes that support flexible data-driven decision-making in the development lifecycle. Most importantly, deep synergies are needed between software engineers, managers, and data scientists. This paper reports on the results of the joint 5th International Workshop on Rapid Continuous Software Engineering (RCoSE 2019) and the 1st International Workshop on Data-Driven Decisions, Experimentation and Evolution (DDrEE 2019), which focuses on the challenges and potential solutions in the area of continuous data-driven software engineering. en_US
dc.language.iso eng en_US
dc.publisher Association for Computing Machinery en_US
dc.relation.ispartofseries ACM SIGSOFT Software Engineering Notes;44 (3), pp. 60-64
dc.rights "© ACM, 2019. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM SIGSOFT Software Engineering Notes, 2019 44 (3), pp. 60-64, en_US
dc.subject continuous software engineering en_US
dc.subject data-driven en_US
dc.subject experimentation en_US
dc.title Continuous data-driven software engineering – towards a research agenda en_US
dc.type info:eu-repo/semantics/article en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.identifier.doi 10.1145/3356773.3356811
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US

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