Automated Feedback Generation for Competition-Level Code

Jialu Zhang, De Li, John Charles Kolesar, Hanyuan Shi, Ruzica Piskac

Abstract

Competitive programming has become a popular way for programmers to test their skills. Competition-level programming problems are challenging in nature, and participants often fail to solve the problem on their first attempt. Some online platforms for competitive programming allow programmers to practice on competition-level problems, and the standard feedback for an incorrect practice submission is the first test case that the submission fails. Often, the failed test case does not provide programmers with enough information to resolve the errors in their code, and they abandon the problem after making several more unsuccessful attempts.

BibTeX

@inproceedings{Zhang-al:ASE22,
  author    = {Jialu Zhang and
               De Li and
               John Charles Kolesar and
               Hanyuan Shi and
               Ruzica Piskac},
  title     = {Automated Feedback Generation for {Competition-Level} Code},
  booktitle = {ASE},
  pages     = {13:1--13:13},
  publisher = {{ACM}},
  year      = {2022},
}

Automated Feedback Generation for Competition-Level Code

Abstract

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