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    CFGExplorer: Designing a Visual Control Flow Analytics System around Basic Program Analysis Operations

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    cfg_2018_explorer_preprint.pdf
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    Author
    Devkota, Sabin
    Isaacs, Katherine E.
    Affiliation
    Univ Arizona, Comp Sci
    Issue Date
    2018-06
    
    Metadata
    Show full item record
    Publisher
    WILEY
    Citation
    Devkota, S. and Isaacs, K. E. (2018), CFGExplorer: Designing a Visual Control Flow Analytics System around Basic Program Analysis Operations. Computer Graphics Forum, 37: 453-464. doi:10.1111/cgf.13433
    Journal
    COMPUTER GRAPHICS FORUM
    Rights
    © 2018 The Author(s). Published by John Wiley & Sons Ltd.
    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
    To develop new compilation and optimization techniques, computer scientists frequently Consult program analysis artifacts such as Control flow graphs (CFGs) and traces of executed instructions. A CFG is a directed graph representing possible execution paths in a program. CFGs are commonly visualized as node-link diagrams while traces are commonly viewed in raw text format. Visualizing and exploring CFGs and traces is challenging because of the complexity and specificity of the operations researchers perform. We present a design study where we collaborate with computer scientists researching dynamic binary analysis and compilation techniques. The research group primarily employs CFGs and traces to reason about and develop new algorithms for program optimization and parallelization. Through questionnaires, interviews, and a year-long observation, we analyzed their use of visualization, noting that the tasks they perform match common subroutines they employ in their techniques. Based on this task analysis, we designed CFGExplorer, a visual analytics system that supports computer scientists with interactions that are integrated with the program structure. We developed a domain-specific graph modification to generate graph layouts that reflect program structure. CFGExplorer incorporates structures such as functions and loops, and uses the correspondence between CFGs and traces to support navigation. We further augment the system to highlight the output of program analysis techniques, facilitating exploration at a higher level. We evaluate the tool through guided sessions and semi-structured interviews as well as deployment. Our collaborators have integrated CFGExplorer into their workflow and use it to reason about programs, develop and debug new algorithms, and share their findings.
    ISSN
    01677055
    DOI
    10.1111/cgf.2018.37.issue-3
    Sponsors
    National Science Foundation [III-1656958]
    Additional Links
    http://doi.wiley.com/10.1111/cgf.2018.37.issue-3
    https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13433
    ae974a485f413a2113503eed53cd6c53
    10.1111/cgf.2018.37.issue-3
    Scopus Count
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    UA Faculty Publications

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