Backward Data-flow Analysis

Backward Data-Flow Analysis is a data-flow analysis technique that computes information about a program's execution state by propagating constraints or facts from the end of a control-flow graph to its beginning, distinguishing it from forward analyses that propagate from the start to the end.

17

Publications

729

Citations

40

Authors

23

Institutions

Publications per year

2017–2026

1

Authors

40

  1. JC
    Jong-Deok Choi

    IBM Research - Thomas J. Watson Research Center, United States

    2 publications · 148 citations

    2

    h-index

  2. SJ
    Shujuan Jiang

    China University of Mining and Technology, China

    2 publications · 76 citations

    2

    h-index

  3. DG
    David Grove

    IBM (United States), United States

    2 publications · 148 citations

    2

    h-index

  4. MH
    Michael Hind

    IBM (United States), United States

    2 publications · 148 citations

    2

    h-index

  5. VS
    Vivek Sarkar

    Rice University, United States

    2 publications · 148 citations

    2

    h-index

1–5 of 40

Venues

  1. 2

    h-index

  2. Frontiers of Structural and Civil Engineering

    1 publications · 19 citations

    1

    h-index

  3. SIAM Journal on Scientific Computing

    1 publications · 37 citations

    1

    h-index

  4. Expert Systems with Applications

    1 publications · 68 citations

    1

    h-index

  5. ACM SIGPLAN Notices

    1 publications · 13 citations

    1

    h-index

1–5