Type Inference

Type Inference is the systematic method within type systems that enables the automatic deduction of the most general type of an expression in a programming language without requiring explicit type annotations, distinguishing it from type checking by deriving rather than verifying type information.

789

Publications

43.3K

Citations

1.1K

Authors

415

Institutions

Publications per year

2017–2026

94

Authors

1.1K

  1. JP
    Jens Palsberg

    University of California, Los Angeles, United States

    25 publications · 1.3K citations

    18

    h-index

  2. JS
    Jeffrey S. Foster

    University of Maryland, College Park, United States

    18 publications · 1.5K citations

    17

    h-index

  3. SP
    Simon Peyton Jones

    Microsoft Research (United Kingdom), United Kingdom

    16 publications · 1.2K citations

    15

    h-index

  4. AA
    Alex Aiken

    Stanford University, United States

    15 publications · 1.6K citations

    14

    h-index

  5. MS
    Martin Sulzmann

    National University of Singapore, Singapore

    15 publications · 856 citations

    14

    h-index

1–5 of 1.1K

Venues

  1. ACM SIGPLAN Notices

    64 publications · 2.5K citations

    28

    h-index

  2. 23

    h-index

  3. Journal of Functional Programming

    31 publications · 1.9K citations

    22

    h-index

  4. Proceedings of the ACM on Programming Languages

    PACMPL · 18 publications · 455 citations

    15

    h-index

  5. Information and Computation

    13 publications · 979 citations

    13

    h-index

1–5