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Dataset Summary

  • This dataset aims to facilitate the creation of sophisticated, multi-turn dialogue datasets focused on coding that could be used for training reasoning Large Language Models (LLMs), particularly for Supervised Fine-Tuning (SFT) and Knowledge Distillation techniques.
  • It also serves as a robust foundation for problem-solving in Large Language Models (LLMs).
  • The dataset includes both accepted and failed solutions from CodeChef Starters Contests.
  • It covers contests up to START contest 196 (Jul 23, 2025).
  • In total, it features 1747 unique problems and 1,522,035 submissions across over 38 different programming languages.
  • (The dataset is not accessible to the public, please do not contact me regarding its access.)

Languages

The problem descriptions are in English. The dataset includes submissions in various programming languages.
Here is a table with the 10 most used languages.

Lang
C++
PYTH 3
JAVA
C
PYPY3
NODEJS
C#
GO
KTLN
rust

Result

The status indicates the outcome of each submission. It contains the result or a score based on the total solved subtasks for the given problem.
Here is a table showing some of the possible results.

Result
100
wrong answer
time limit exceeded
compilation error
runtime error(OTHER)
runtime error(SIGSEGV)

Data Splits

There are no splits (Only training).

Dataset Creation

Jul of 2025

Source Data

The source of the dataset is CodeChef's contests

Annotations

The dataset includes the following columns:

  • contest_code: CODE of the contest (e.g., START1).
  • statement: Markdown explanation of the problem.
  • dificulty: Difficulty given to the problem (e.g. 1533).
  • title: Title of the problem.
  • language: Programming language used for the solution (see previous table for details).
  • result: Outcome of the submission (see previous table for details).
  • execution_time: Time taken by the submission in milliseconds.
  • execution_memory: Memory used by the submission in kilobytes
  • code: Code that solves the problem.

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