Automatic Error Analysis

Automatic Error Analysis is a systematic methodological framework within the field of error analysis that distinguishes itself by enabling the computational identification, classification, and interpretation of errors in data or model outputs without continuous human intervention.

120

Publications

4.7K

Citations

366

Authors

152

Institutions

Publications per year

2017–2026

19

Authors

366

  1. MR
    Martin Rinard

    Massachusetts Institute of Technology, United States

    6 publications · 343 citations

    6

    h-index

  2. MP
    Maja Popović

    German Research Centre for Artificial Intelligence, Germany

    6 publications · 329 citations

    6

    h-index

  3. SS
    Stelios Sidiroglou-Douskos

    Massachusetts Institute of Technology, United States

    5 publications · 275 citations

    5

    h-index

  4. FL
    Fan Long

    Massachusetts Institute of Technology, United States

    5 publications · 275 citations

    5

    h-index

  5. HN
    Hermann Ney

    RWTH Aachen University, Germany

    4 publications · 245 citations

    4

    h-index

1–5 of 366

Venues

  1. Communications of the ACM

    4 publications · 109 citations

    4

    h-index

  2. Proceedings of the ACM on Programming Languages

    PACMPL · 2 publications · 102 citations

    2

    h-index

  3. ReCALL

    2 publications · 70 citations

    2

    h-index

  4. Journal of Systems and Software

    JSS · 2 publications · 208 citations

    2

    h-index

  5. ACM SIGSOFT Software Engineering Notes

    SEN · 2 publications · 33 citations

    2

    h-index

1–5