Token Flow Analysis

Token Flow Analysis is a dataflow modeling method that analyzes the propagation and transformation of discrete data units, or tokens, through a computational system to determine correctness, efficiency, and resource usage in processing workflows.

24

Publications

1.2K

Citations

51

Authors

28

Institutions

Publications per year

2017–2026

1

Authors

51

  1. EA
    Edward A. Lee

    University of California, Berkeley, United States

    4 publications · 593 citations

    4

    h-index

  2. JB
    Joseph Buck

    Synopsys (United States), United States

    3 publications · 555 citations

    3

    h-index

  3. AW
    Anthony Waller

    Lanner Group (United Kingdom), United Kingdom

    2 publications · 24 citations

    2

    h-index

  4. MP
    Martin P. Clark

    Lanner Group (United Kingdom), United Kingdom

    2 publications · 24 citations

    2

    h-index

  5. LE
    Les Enstone

    Lanner Group (United Kingdom), United Kingdom

    2 publications · 24 citations

    2

    h-index

1–5 of 51

Venues

  1. Parallel Processing Letters

    1 publications · 17 citations

    1

    h-index

  2. Journal of Medical Internet Research

    1 publications · 12 citations

    1

    h-index

  3. Information Sciences

    1 publications · 16 citations

    1

    h-index

  4. Winter Simulation Conference

    Conference · 1 publications · 13 citations

    1

    h-index

  5. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 1 publications · 113 citations

    1

    h-index

1–5