metadata

license: cdla-permissive-2.0
task_categories:
  - text-generation
  - text2text-generation
  - other
tags:
  - code
  - fstar
  - popai
pretty_name: PoPAI-FStarDataSet
size_categories:
  - 10K<n<100K
language:
  - code
  - fst

Proof Oriented Programming with AI (PoPAI) - FStarDataSet

This dataset contains programs and proofs in F* proof-oriented programming language. The data, proposed in Towards Neural Synthesis for SMT-Assisted Proof-Oriented Programming. is an archive of source code, build artifacts, and metadata assembled from eight different F⋆-based open source projects on GitHub.

Data Source

The raw data in this project are collected from eight open-source F* reposiroties in GitHib

FStar: The F⋆ compiler itself, including its standard libraries and examples.
Karamel: A transpiler from a subset of F⋆ called Low* to C, including libraries to work with a model of C types and control structures, e.g., for- and while-loops.
EverParse: A parser generator for binary formats, used in various large scale systems, e.g., the Windows kernel.
HACL*: A library of verified cryptographic algorithms, including ValeCrypt, a library of verified assembly code, as well as EverCrypt, a cryptographic provider, including code deployed in Linux, Firefox, and Python.
Merkle-tree: A verified, incremental Merkle tree, designed for use in Azure CCF, a confidential computing system.
Steel: A concurrent separation logic library, with proofs of data structures and concurrency primitives.
miTLS-F*: A partially verified reference implementation of the TLS protocol.
EverQuic-Crypto: A verified implementation of header and packet protection for the QUIC protocol.

Primary-Objective

Data Format

Each of the examples in this dataset are organized as dictionaries with the following schema

{
    "file_name": <str: Name of the file>,
    "name": <str: name of the example, can be used to uniquely identify the example>,
    "original_source_type": <str: actual source type, to be used for type checking>,
    "source_type": <str: modified source type, to be used to formulate prompt>,
    "source_definition": <str: target definition>,
    "source": <dict: contains metadata acout the source of this example, including project_name, git url, git sha, etc.>,
    "source_range": <dict: metadata containing start and end lines and columns of this definition in the source file>,
    "file_context": <str: extracted file context upto the point of current definition>, 
    "dependencies": <dict: build dependencies for this file>,
    "opens_and_abbrevs": <list[dict]: List of opened modules and abbreviated modules in the file, necessry for evaluating.>,
    "vconfig": <dict: variour buils configuration for this definition>,
    "interleaved": <bool: whether this definition is interleaved with another>,
    "verbose_type": <str: the verbose type of this definition as resolved by the type checker>,
    "effect": <str: effect>,
    "effect_flags": <list[str]: any effect flags>,
    "mutual_with": <list: if this definition is mutually recursive with other, list of those names>,
    "ideal_premises": <list[str]: Other definitions that are used in the ground truth definition>,
    "proof_features": <list[str]>,
    "is_simple_lemma": <bool/null>,
    "is_div": <bool: if this definition is divergent>,
    "is_proof": <bool>,
    "is_simply_typed": <bool>,
    "is_type": <bool/null>,
    "partial_definition": <str>,
    "completed_definiton": <str>,
    "isa_cross_project_example": <bool: if this example belongs to cross-project evaluation set>
}

Usage

Input

Output

Evaluation on this dataset