# The CodRep Machine Learning on Source Code Competition

arXiv: https://arxiv.org/abs/1807.03200 · HTML: https://mlsanity.com/paper/1807.03200/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Jul 2018.

## Built on by (most cited first, 4 of 4)

- [Natural Language Generation and Understanding of Big Code for AI-Assisted Programming: A Review](https://mlsanity.com/paper/2307.02503/) (2023)
- [RunBugRun -- An Executable Dataset for Automated Program Repair](https://mlsanity.com/paper/2304.01102/) (2023)
- [MIXCODE: Enhancing Code Classification by Mixup-Based Data Augmentation](https://mlsanity.com/paper/2210.03003/) (2022)
- [CodeLL: A Lifelong Learning Dataset to Support the Co-Evolution of Data and Language Models of Code](https://mlsanity.com/paper/2312.12492/) (2023)

## Abstract (arXiv)

CodRep is a machine learning competition on source code data. It is carefully designed so that anybody can enter the competition, whether professional researchers, students or independent scholars, without specific knowledge in machine learning or program analysis. In particular, it aims at being a common playground on which the machine learning and the software engineering research communities can interact. The competition has started on April 14th 2018 and has ended on October 14th 2018. The CodRep data is hosted at https://github.com/KTH/CodRep-competition/.