The CodRep Machine Learning on Source Code Competition
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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/.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Jul 2018.
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Citing papers per year: 2022: 1; 2023: 3.
4 papers.
- 2023Natural Language Generation and Understanding of Big Code for AI-Assisted Programming: A Reviewcited by 32
- 2023RunBugRun -- An Executable Dataset for Automated Program Repaircited by 10
- 2022MIXCODE: Enhancing Code Classification by Mixup-Based Data Augmentationcited by 4
- 2023CodeLL: A Lifelong Learning Dataset to Support the Co-Evolution of Data and Language Models of Codecited by 0
- 2023CodeLL: A Lifelong Learning Dataset to Support the Co-Evolution of Data and Language Models of Code20 Dec 2023
- 2023Natural Language Generation and Understanding of Big Code for AI-Assisted Programming: A Review4 Jul 2023
- 2023RunBugRun -- An Executable Dataset for Automated Program Repair3 Apr 2023
- 2022MIXCODE: Enhancing Code Classification by Mixup-Based Data Augmentation6 Oct 2022