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arXiv · 2503.18251

COFO: COdeFOrces dataset for Program Classification, Recognition and Tagging

Kuldeep Gautam·S. VenkataKeerthy·Ramakrishna Upadrasta
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Abstract

In recent years, a lot of technological advances in computer science have aided software programmers to create innovative and real-time user-friendly software. With the creation of the software and the urging interest of people to learn to write software, there is a large collection of source codes that can be found on the web, also known as Big Code, which can be used as a source of data for driving the machine learning applications tending to solve certain software engineering problems. In this paper, we present COFO, a dataset consisting of 809 classes/problems with a total of 369K source codes written in C, C++, Java, and Python programming languages, along with other metadata such as code tags, problem specification, and input-output specifications. COFO has been scraped from the openly available Codeforces website using a selenium-beautifulsoup-python based scraper. We envision that this dataset can be useful for solving machine learning-based problems like program classification/recognition, tagging, predicting program properties, and code comprehension.

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Kuldeep Gautam, S. VenkataKeerthy, Ramakrishna Upadrasta. 2025-03-24. COFO: COdeFOrces dataset for Program Classification, Recognition and Tagging. https://arxiv.org/abs/2503.18251

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