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        <title>Natural Language Annotations for Reasoning about Program Semantics</title>
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            <namePart type="given">Houda</namePart>
            <namePart type="family">Bouamor</namePart>
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        <name type="personal">
            <namePart type="given">Juan</namePart>
            <namePart type="family">Pino</namePart>
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        <name type="personal">
            <namePart type="given">Kalika</namePart>
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    <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 .</abstract>
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%0 Conference Proceedings
%T Natural Language Annotations for Reasoning about Program Semantics
%A Zocca, Marco
%Y Bouamor, Houda
%Y Pino, Juan
%Y Bali, Kalika
%S Findings of the Association for Computational Linguistics: EMNLP 2023
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F zocca-2023-natural
%X 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 .
%R 10.18653/v1/2023.findings-emnlp.601
%U https://aclanthology.org/2023.findings-emnlp.601/
%U https://doi.org/10.18653/v1/2023.findings-emnlp.601
%P 8961-8966

Markdown (Informal)

[Natural Language Annotations for Reasoning about Program Semantics](https://aclanthology.org/2023.findings-emnlp.601/) (Zocca, Findings 2023)

• Natural Language Annotations for Reasoning about Program Semantics (Zocca, Findings 2023)

ACL

• Marco Zocca. 2023. Natural Language Annotations for Reasoning about Program Semantics. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 8961–8966, Singapore. Association for Computational Linguistics.