Constraint Generation

Constraint Generation is a methodological process in symbolic execution that systematically derives path constraints from program execution paths by collecting conditional expressions encountered during exploration, distinguishing it from other program analysis techniques through its focus on generating logical formulas representing feasible execution paths.

444

Publications

29.8K

Citations

1.2K

Authors

400

Institutions

Publications per year

2017–2026

184

Authors

1.2K

  1. MS
    Mohammad Shahidehpour

    Illinois Institute of Technology, United States

    12 publications · 1.5K citations

    12

    h-index

  2. JW
    Jianhui Wang

    Argonne National Laboratory, United States

    10 publications · 1.2K citations

    10

    h-index

  3. CW
    Cheng Wang

    North China Electric Power University, China

    8 publications · 413 citations

    8

    h-index

  4. BZ
    Bo Zeng

    University of Pittsburgh, United States

    8 publications · 2.2K citations

    8

    h-index

  5. WW
    Wei Wei

    Tsinghua University, China

    8 publications · 638 citations

    8

    h-index

1–5 of 1.2K

Venues

  1. IEEE Transactions on Power Systems

    46 publications · 4.5K citations

    37

    h-index

  2. IEEE Transactions on Sustainable Energy

    TSTE · 23 publications · 2.4K citations

    23

    h-index

  3. IEEE Transactions on Smart Grid

    23 publications · 2.5K citations

    22

    h-index

  4. 6

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 6 publications · 131 citations

    6

    h-index

1–5