saroshq/minitorch-graphqa

MiniTorch GraphQA

A dataset of 100 developer-style questions over the MiniTorch codebase, designed for structured, graph-based code reasoning. Each question maps to a precise function or class in the source code and is intended for use with symbolic reasoning models like the Tiny Recursion Model (TRM).

Intended Use

This dataset is designed to evaluate lightweight, recursive reasoning agents that operate over retrieved subgraphs of code (e.g., 10-node neighborhoods). It is not for code generation or language modeling.

Data Format

Each line in questions.jsonl is a JSON object:

{
  "id": "minitorch-001",
  "question": "Which function computes the derivative of scalar addition?",
  "answer_node": "minitorch.scalar.Scalar.add_back",
  "module": 1,
  "reasoning_type": "autodiff"
}
    id: unique identifier
    question: natural language developer question
    answer_node: fully qualified name of the ground-truth function/class
    module: MiniTorch module number (0–6)
    reasoning_type: category of reasoning required
     

License 

MIT License.
Citation 

If you use this dataset, please cite: 

@dataset{minitorch_graphqa_2025,
  author = {Sarosh Quraishi},
  title = {MiniTorch GraphQA: A Symbolic Reasoning Benchmark for Code},
  year = {2025},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/saroshq/minitorch-graphqa}
}
 
 
Acknowledgements 

    MiniTorch: https://github.com/atgctg/minitorch