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    • Unit and Regression Tests of Scientific Software: A Study on SWMM

    Metadata Updated: March 7, 2022

    Testing helps assure software quality by executing programs and uncovering bugs. Scientific software developers often find it challenging to carry out systematic and automated testing due to reasons such as inherent model uncertainties and complex floating-point computations. Extending the recent work on analyzing the unit tests written by the developers of the Storm Water Management Model (SWMM), we report in this paper the investigation of both unit and regression tests of SWMM. The results show that the 1,458 SWMM tests have a 54.0% code coverage and an 82.4% User’s Manual coverage. Meanwhile, an examination of eight regression tests from a test set shows a 79.5% code coverage and a near 100% User’s Manual coverage. We also observe a “getter-setter-getter” testing pattern from the SWMM unit tests and suggest a diversified way of designing or adopting regression tests.

    This dataset is associated with the following publication: Peng, Z., X. Lin, M. Simon, and N. Niu. Unit and Regression Tests of Scientific Software: A Study on SWMM. Journal of Computational Science. Elsevier B.V., Amsterdam, NETHERLANDS, 53: 101347, (2021).

    Access & Use Information

    Public: This dataset is intended for public access and use. License: See this page for license information.

    Downloads & Resources

    References

    https://doi.org/10.1016/j.jocs.2021.101347
    https://pasteur.epa.gov/uploads/10.23719/1519338/documents/SWMM%20OpenCppCoverage%20Step.pdf

    Dates

    Metadata Created Date April 21, 2021
    Metadata Updated Date March 7, 2022

    Metadata Source

    Harvested from EPA ScienceHub

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date April 21, 2021
    Metadata Updated Date March 7, 2022
    Publisher U.S. EPA Office of Research and Development (ORD)
    Maintainer
    Identifier https://doi.org/10.23719/1519338
    Data Last Modified 2020-09-08
    Public Access Level public
    Bureau Code 020:00
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Data Dictionary https://pasteur.epa.gov/uploads/10.23719/1519338/documents/Unit%20and%20Regression%20Tests%20of%20Scientific%20Softwaredatadictionary.docx
    Data Dictionary Type application/vnd.openxmlformats-officedocument.wordprocessingml.document
    Harvest Object Id a1731576-e665-4597-acd3-1db78ada59f1
    Harvest Source Id 04b59eaf-ae53-4066-93db-80f2ed0df446
    Harvest Source Title EPA ScienceHub
    License https://pasteur.epa.gov/license/sciencehub-license.html
    Program Code 020:096
    Publisher Hierarchy U.S. Government > U.S. Environmental Protection Agency > U.S. EPA Office of Research and Development (ORD)
    Related Documents https://doi.org/10.1016/j.jocs.2021.101347, https://pasteur.epa.gov/uploads/10.23719/1519338/documents/SWMM%20OpenCppCoverage%20Step.pdf
    Source Datajson Identifier True
    Source Hash f88f12d49e18a1207198f4e3bfc3f729ea1fac58
    Source Schema Version 1.1

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