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Towards a Trustworthy Semantics-Based Language Framework via Proof Generation

Authors: Xiaohong; Zhengyao; Thai; Grigore;

Towards a Trustworthy Semantics-Based Language Framework via Proof Generation

Abstract

This is the artifact evaluation Docker image of our paper, Towards a Trustworthy Semantics-Based Language Framework via Proof Generation. The abstract of the paper reads: We pursue the vision of an ideal language framework, where programming language designers only need to define the formal syntax and semantics of their languages, and all language tools are automatically generated by the framework. Due to the complexity of such a language framework, it is a big challenge to ensure its trustworthiness and to establish the correctness of the autogenerated language tools. In this paper, we propose an innovative approach based on proof generation. The key idea is to generate proof objects as correctness certificates for each individual task that the language tools conduct, on a case-by-case basis, and use a trustworthy proof checker to check the proof objects. This way, we avoid formally verifying the entire framework, which is practically impossible, and thus can make the language framework both practical and trustworthy. As a first step, we formalize program execution as mathematical proofs and generate their complete proof objects. The experimental result shows that the performance of our proof object generation and proof checking is very promising.

Keywords

Matching Logic, Formal Language Framework, Proof Object Generation

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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