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Title:Towards a Trustworthy Semantics-Based Language Framework via Proof Generation
Author(s):Xiaohong Chen; Zhengyao Lin; Minh-Thai Trinh; Grigore Rosu
Subject(s):Semantic framework
Proof generation
Proof checking
Abstract: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.
Issue Date:2021-04
Genre:Technical Report
Date Available in IDEALS:2021-05-01

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