Automated Code Feedback

Automated Code Feedback is a computational method that systematically analyzes source code to generate immediate, objective, and actionable assessments of its quality, correctness, or adherence to predefined standards without human intervention.

103

Publications

5.1K

Citations

313

Authors

124

Institutions

Publications per year

2017–2026

58

Variants

Automated Programming Feedback

Authors

313

  1. CB
    Christian Bird

    Microsoft (United States), United States

    5 publications · 618 citations

    5

    h-index

  2. SH
    Stephen H. Edwards

    Virginia Tech, United States

    5 publications · 454 citations

    5

    h-index

  3. RS
    Rishabh Singh

    Microsoft (United States), United States

    4 publications · 510 citations

    4

    h-index

  4. JS
    Jaime Spacco

    Knox College, United States

    3 publications · 307 citations

    3

    h-index

  5. WP
    William Pugh

    University of Maryland, College Park, United States

    3 publications · 241 citations

    3

    h-index

1–5 of 313

Venues

  1. Journal of computing sciences in colleges

    3 publications · 45 citations

    3

    h-index

  2. Empirical Software Engineering

    3 publications · 83 citations

    3

    h-index

  3. ACM SIGCSE Bulletin

    2 publications · 378 citations

    2

    h-index

  4. Computer Applications in Engineering Education

    CAE · 2 publications · 53 citations

    2

    h-index

  5. arXiv (Cornell University)

    Repository · 2 publications · 53 citations

    2

    h-index

1–5