Demand-driven Data-flow Analysis

Demand-Driven Data-Flow Analysis is a data-flow analysis technique that belongs to the class of on-demand analysis methods, distinguished by its computation of data-flow facts for specific program points or queries of interest only when explicitly required, rather than computing global summaries across all program points.

11

Publications

638

Citations

18

Authors

9

Institutions

Publications per year

2017–2026

1

Variants

Demand-driven Data Flow Analysis

Authors

18

  1. RG
    Rajiv Gupta

    University of California, Riverside, United States

    4 publications · 243 citations

    4

    h-index

  2. ML
    Mary Lou Soffa

    University of Pittsburgh, United States

    3 publications · 224 citations

    3

    h-index

  3. ED
    Evelyn Duesterwald

    Hewlett-Packard (United States), United States

    3 publications · 224 citations

    3

    h-index

  4. MS
    Mooly Sagiv

    Tel Aviv University, Israel

    2 publications · 198 citations

    2

    h-index

  5. TR
    Thomas Reps

    University of Wisconsin–Madison, United States

    2 publications · 198 citations

    2

    h-index

1–5 of 18

Venues

  1. IEEE Transactions on Software Engineering

    TSE · 1 publications · 52 citations

    1

    h-index

  2. ACM SIGSOFT Software Engineering Notes

    SEN · 1 publications · 27 citations

    1

    h-index

  3. 1

    h-index

  4. Parallel Processing Letters

    1 publications · 19 citations

    1

    h-index

  5. International Conference on Software Engineering

    Conference · 1 publications · 23 citations

    1

    h-index

1–5