README.md

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
  splits:
    - name: code_from_tc_mcq
      num_bytes: 301760025
      num_examples: 99946
    - name: code_to_tc_mcq
      num_bytes: 120263200
      num_examples: 99896
    - name: tc_direct
      num_bytes: 65143462
      num_examples: 62185
  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)