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metadata
pretty_name: Code Time Complexity Tasks
configs:
- config_name: default
data_files:
- split: train
path: data/*.parquet
- config_name: code_from_tc_mcq
data_files:
- split: train
path: data/code_from_tc_mcq*.parquet
- config_name: code_to_tc_mcq
data_files:
- split: train
path: data/code_to_tc_mcq*.parquet
- config_name: tc_direct
data_files:
- split: train
path: data/tc_direct*.parquet
size_categories:
- 100K<n<1M
dataset_info:
features:
- name: data_source
dtype: string
- name: prompt
list:
- name: content
dtype: string
- name: role
dtype: string
- name: ability
dtype: string
- name: reward_model
struct:
- name: extraction_method
dtype: string
- name: ground_truth
dtype: string
- name: style
dtype: string
- name: extra_info
struct:
- name: comp
dtype: string
- name: idx
dtype: string
- name: problem_id
dtype: string
- name: task_type
dtype: string
download_size: 476966917
dataset_size: 487166687
Code Time Complexity prediction
Sourced from BigOBench, using a subset of the N-most commonly occuring time complexities in the dataset
Three tasks:
- tc_direct: Directly predict the time complexity as O(X) given the code
- code_to_tc_mcq: Select the correct time complexity from four options, given the code
- code_from_tc_mcq: Given a time complexity, select the code with that time complexity from four options.
| Complexity |
|---|
| O(1) |
| O(logn) |
| O(n) |
| O(n+m) |
| O(nlogn) |
| O(nlogn+m) |
| O(n+mlogm) |
| O(n*m) |
| O(n**2) |