Automated Program Synthesis

Automated Program Synthesis is a computational method within evolutionary computation that generates executable programs as solutions by automatically searching a program space guided by a fitness function, distinguished from other synthesis approaches by its reliance on evolutionary mechanisms such as mutation, crossover, and selection.

370

Publications

19.1K

Citations

769

Authors

246

Institutions

Publications per year

2017–2026

171

Authors

769

  1. AS
    Armando Solar-Lezama

    Massachusetts Institute of Technology, United States

    22 publications · 1.5K citations

    16

    h-index

  2. SG
    Sumit Gulwani

    Microsoft (United States), United States

    19 publications · 1.4K citations

    16

    h-index

  3. TH
    Thomas Helmuth

    Hampshire College, United States

    11 publications · 357 citations

    11

    h-index

  4. RS
    Rishabh Singh

    Microsoft (United States), United States

    10 publications · 626 citations

    10

    h-index

  5. YF
    Yu Feng

    The University of Texas at Austin, United States

    10 publications · 429 citations

    10

    h-index

1–5 of 769

Venues

  1. arXiv (Cornell University)

    Repository · 40 publications · 2K citations

    23

    h-index

  2. Proceedings of the ACM on Programming Languages

    PACMPL · 21 publications · 866 citations

    17

    h-index

  3. ACM SIGPLAN Notices

    20 publications · 627 citations

    15

    h-index

  4. Proceedings of the Genetic and Evolutionary Computation Conference

    Conference · 10 publications · 356 citations

    10

    h-index

  5. International Joint Conference on Artificial Intelligence

    Conference · 6 publications · 137 citations

    6

    h-index

1–5