EMNLP 2023short findings0 citations

Natural Language Annotations for Reasoning about Program Semantics

Marco Zocca

Abstract

By grounding natural language inference in code (and vice versa), researchers aim to create programming assistants that explain their work, are "coachable" and can surface any gaps in their reasoning. Can we deduce automatically interesting properties of programs from their syntax and common-sense annotations alone, without resorting to static analysis? How much of program logic and behaviour can be captured in natural language? To stimulate research in this direction and attempt to answer these questions we propose HTL, a dataset and protocol for annotating programs with natural language predicates at a finer granularity than code comments and without relying on internal compiler representations. The dataset is available at the following address: https://doi.org/10.5281/zenodo.7893113 .

program understandingnatural language reasoningdataset
BibTeX
@inproceedings{
zocca2023natural,
title={Natural Language Annotations for Reasoning about Program Semantics},
author={Marco Zocca},
booktitle={The 2023 Conference on Empirical Methods in Natural Language Processing},
year={2023},
url={https://openreview.net/forum?id=RndkyLWLHc}
}