--- license: apache-2.0 task_categories: - text-generation - text2text-generation language: - en tags: - code size_categories: - n<1K --- # DafnyBench: A Benchmark for Formal Software Verification Dataset & code for our paper [DafnyBench: A Benchmark for Formal Software Verification]()
## Overview 📊 DafnyBench is the largest benchmark of its kind for training and evaluating machine learning systems for formal software verification, with over 750 Dafny programs.

## Usage 💻 - Dataset: The dataset for DafnyBench (with ~782 programs) could be found in the `DafnyBench` directory, which contains the `ground_truth` set & the `hints_removed`set (with compiler hints, i.e. annoataions, removed). - Evaluation: Evaluate LLMs on DafnyBench by asking models to fill in missing hints in a test file from the `hints_removed` set and checking if the reconstructed program could by verified by Dafny. Please refer to the `eval` directory.



## Set Up for Evaluation 🔧 1. Install Dafny on your machine by following [this tutorial](https://dafny.org/dafny/Installation) 2. Clone & `cd` into this repository 3. Set up environment by running the following lines: ``` python -m venv stats source stats/bin/activate pip install -r requirements.txt cd eval ``` 4. Set up environment variable for the root directory: ``` export DAFNYBENCH_ROOT= ``` 5. Set up environment variable for path to Dafny executable on your machine (for example, `/opt/homebrew/bin/Dafny`): ``` export DAFNY_PATH= ``` 6. If you're evaluating an LLM through API access, set up API key. For example: ``` export OPENAI_API_KEY= ``` 7. You can choose to evaluate an LLM on a single test program, such as: ``` python fill_hints.py --model "gpt-4o" --test_file "Clover_abs_no_hints.dfy" --feedback_turn 3 --dafny_path "$DAFNY_PATH" ``` or evaluate on the entire dataset: ``` export model_to_eval='gpt-4o' ./run_eval.sh ```
## Contents 📁 - `DafnyBench` - A collection of 782 Dafny programs. Each program has a `ground_truth` version that is fully verified with Dafny & a `hints_removed` version that has hints (i.e. annotations) removed - `eval` - Contains scripts to evaluate LLMs on DafnyBench - `results` - `results_summary` - Dataframes that summarize LLMs' success on every test program - `reconstructed_files` - LLM outputs with hints filled back in - `analysis` - Contains a notebook for analyzing the results