Optimal Code Generation

Optimal Code Generation is a code generation method that belongs to the class of instruction selection techniques in compiler design, distinguished by its goal of producing target code that is provably minimal or least-cost with respect to a given cost metric, such as execution time, code size, or resource usage.

103

Publications

5.1K

Citations

206

Authors

98

Institutions

Publications per year

2017–2026

11

Authors

206

  1. AV
    Alfred V. Aho

    Princeton University, United States

    5 publications · 321 citations

    5

    h-index

  2. AB
    Andrzej Bednarski

    Linköping University, Sweden

    5 publications · 100 citations

    5

    h-index

  3. JD
    Jeffrey D. Ullman

    Stanford University, United States

    4 publications · 351 citations

    4

    h-index

  4. SC
    S. C. Johnson

    McGill University, Canada

    4 publications · 303 citations

    4

    h-index

  5. ME
    Mattias Eriksson

    Lund University, Sweden

    3 publications · 69 citations

    3

    h-index

1–5 of 206

Venues

  1. ACM SIGPLAN Notices

    7 publications · 172 citations

    7

    h-index

  2. Communications of the ACM

    6 publications · 355 citations

    6

    h-index

  3. IEEE Transactions on Information Theory

    6 publications · 389 citations

    6

    h-index

  4. Journal of the ACM

    JACM · 4 publications · 585 citations

    4

    h-index

  5. KTH Publication Database DiVA (KTH Royal Institute of Technology)

    Repository · 2 publications · 52 citations

    2

    h-index

1–5