Original Research ARTICLE

Front. Neuroinform., 03 January 2013 | doi: 10.3389/fninf.2012.00031

Increasing quality and managing complexity in neuroinformatics software development with continuous integration

  • 1Institute of Neuroscience and Medicine (INM-6), Computational and Systems Neuroscience, Jülich Research Center, Jülich, Germany
  • 2Simulation Laboratory Neuroscience – Bernstein Facility for Simulation and Database Technology, Institute for Advanced Simulation, Jülich Research Center, Jülich Aachen Research Alliance, Jülich, Germany
  • 3Faculty of Biology, Albert-Ludwig University of Freiburg, Freiburg im Breisgau, Germany
  • 4Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr-University Bochum, Bochum, Germany
  • 5Bernstein Center Freiburg, Albert-Ludwig University of Freiburg, Freiburg im Breisgau, Germany

High quality neuroscience research requires accurate, reliable and well maintained neuroinformatics applications. As software projects become larger, offering more functionality and developing a denser web of interdependence between their component parts, we need more sophisticated methods to manage their complexity. If complexity is allowed to get out of hand, either the quality of the software or the speed of development suffer, and in many cases both. To address this issue, here we develop a scalable, low-cost and open source solution for continuous integration (CI), a technique which ensures the quality of changes to the code base during the development procedure, rather than relying on a pre-release integration phase. We demonstrate that a CI-based workflow, due to rapid feedback about code integration problems and tracking of code health measures, enabled substantial increases in productivity for a major neuroinformatics project and additional benefits for three further projects. Beyond the scope of the current study, we identify multiple areas in which CI can be employed to further increase the quality of neuroinformatics projects by improving development practices and incorporating appropriate development tools. Finally, we discuss what measures can be taken to lower the barrier for developers of neuroinformatics applications to adopt this useful technique.

Keywords: software development, testing, process management, quality control, complexity management

Citation: Zaytsev YV and Morrison A (2013) Increasing quality and managing complexity in neuroinformatics software development with continuous integration. Front. Neuroinform. 6:31. doi: 10.3389/fninf.2012.00031

Received: 23 September 2012; Accepted: 12 December 2012;
Published online: 03 January 2013.

Edited by:

Andrew P. Davison, CNRS, France

Reviewed by:

Yaroslav O. Halchenko, Dartmouth College, USA
Gael Varoquaux, INRIA, France
Raphael Ritz, Karolinska Institutet, Sweden

Copyright © 2013 Zaytsev and Morrison. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.

*Correspondence: Yury V. Zaytsev, Simulation Laboratory Neuroscience – Bernstein Facility for Simulation and Database Technology, Institute for Advanced Simulation, Jülich Research Center, Jülich Aachen Research Alliance, Jülich, Germany. e-mail: zaytsev@fz-juelich.de

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