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Lightweight Software Process Improvement Using Productivity and Sustainability Improvement Planning (PSIP)

Part of the Communications in Computer and Information Science book series (CCIS,volume 1190)

Abstract

Productivity and Sustainability Improvement Planning (PSIP) is a lightweight, iterative workflow that allows software development teams to identify development bottlenecks and track progress to overcome them. In this paper, we present an overview of PSIP and how it compares to other software process improvement (SPI) methodologies, and provide two case studies that describe how the use of PSIP led to successful improvements in team effectiveness and efficiency.

Keywords

  • Software development
  • Software engineering
  • Software process improvement

E. Gonsiorowski, R. Gupta, R. Milewicz, J. D. Moulton, G. R. Watson, J. Willenbring,

R. J. Zamora, E. M. Raybourn—contributed equally to this work.

R. J. Zamora—work was conducted while employed by Argonne National Laboratory.

Under the terms of Contract DE-NA0003525, there is a non-exclusive license for use of this work by or on behalf of the U.S. Government.

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Fig. 1.
Fig. 2.
Fig. 3.

Notes

  1. 1.

    https://bssw.io/psip.

  2. 2.

    https://bssw.io.

  3. 3.

    https://bssw.io/events/best-practices-for-hpc-software-developers-webinar-series.

  4. 4.

    See https://bssw.io/psip for further elaboration.

  5. 5.

    https://www.exascaleproject.org/project/exaalt-molecular-dynamics-at-the-exascale-materials-science.

  6. 6.

    Exascale Onboarding training portal: https://sites.google.com/view/hpc-training-base/home.

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Acknowledgements

Special thanks to Lois McInnes (ANL) and the members of IDEAS-ECP. Thanks to PSIP partners Danny Perez (LANL), Art Voter (LANL), Christoph Junhans (LANL), and Pavan Balaji (ANL). Images used by permission.

This work was supported by the U.S. Department of Energy Office of Science, Office of Advanced Scientific Computing Research (ASCR), Office of Biological and Environmental Research (BER), and by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration.

This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2019-9693 C.

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Correspondence to Elaine M. Raybourn .

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Heroux, M.A. et al. (2020). Lightweight Software Process Improvement Using Productivity and Sustainability Improvement Planning (PSIP). In: Juckeland, G., Chandrasekaran, S. (eds) Tools and Techniques for High Performance Computing. HUST SE-HER WIHPC 2019 2019 2019. Communications in Computer and Information Science, vol 1190. Springer, Cham. https://doi.org/10.1007/978-3-030-44728-1_6

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  • DOI: https://doi.org/10.1007/978-3-030-44728-1_6

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