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    Preserving Command Line Workflow for a Package Management System Using ASCII DAG Visualization

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    Final Accepted Manuscript
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    Author
    Isaacs, Katherine E
    Gamblin, Todd
    Affiliation
    Univ Arizona, Dept Comp Sci
    Issue Date
    2019-09
    Keywords
    Software visualization
    information visualization
    command line interface
    
    Metadata
    Show full item record
    Publisher
    IEEE COMPUTER SOC
    Citation
    K. E. Isaacs and T. Gamblin, "Preserving Command Line Workflow for a Package Management System Using ASCII DAG Visualization," in IEEE Transactions on Visualization and Computer Graphics, vol. 25, no. 9, pp. 2804-2820, 1 Sept. 2019. doi: 10.1109/TVCG.2018.2859974
    Journal
    IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
    Rights
    © 2018 IEEE.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    Package managers provide ease of access to applications by removing the time-consuming and sometimes completely prohibitive barrier of successfully building, installing, and maintaining the software for a system. A package dependency contains dependencies between all packages required to build and run the target software. Package management system developers, package maintainers, and users may consult the dependency graph when a simple listing is insufficient for their analyses. However, users working in a remote command line environment must disrupt their workflow to visualize dependency graphs in graphical programs, possibly needing to move files between devices or incur forwarding lag. Such is the case for users of Spack, an open source package management system originally developed to ease the complex builds required by supercomputing environments. To preserve the command line workflow of Spack, we develop an interactive ASCII visualization for its dependency graphs. Through interviews with Spack maintainers, we identify user goals and corresponding visual tasks for dependency graphs. We evaluate the use of our visualization through a command line-centered study, comparing it to the system's two existing approaches. We observe that despite the limitations of the ASCII representation, our visualization is preferred by participants when approached from a command line interface workflow.
    ISSN
    1077-2626
    PubMed ID
    30047887
    DOI
    10.1109/TVCG.2018.2859974
    Version
    Final accepted manuscript
    Sponsors
    U.S. Department of Energy by Lawrence Livermore National Laboratory [DE-AC52-07NA27344, LLNL-JRNL-746358]
    ae974a485f413a2113503eed53cd6c53
    10.1109/TVCG.2018.2859974
    Scopus Count
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    UA Faculty Publications

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