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Effectively Propositional Higher-Order Functional Programming
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AI
DOI：10.1145/3798259.png)
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Abstract
En 中文
Decidable automation is a key feature of program verification tools, which makes them easier for non-expert developers to use and understand. Unfortunately, decidable fragments of logic are very restrictive, and not ideal for the expression of idiomatic programs. The decidable Extended EPR fragment, combined with an encoding technique called relational abstraction, has seen wide use for its ability to handle both quantifiers and uninterpreted functions. However, the complexity of the relational abstraction encoding, combined with its inherent incompleteness, still poses a significant obstacle to non-experts. In this paper, we show that Extended EPR and relational abstraction can be deployed to achieve decidable, quantified verification within a familiar, principled domain: a higher-order, purely-functional programming language. We observe that, by defining the semantics of our language in terms of partial functions, we obtain a well-behaved, three-valued logic that matches the behavior of the relational abstraction encoding while hiding its complexity. We demonstrate that our prototype implementation can ergonomically replicate EPR-based program verification benchmarks and verify recursive programs on inductive datatypes.
Keywords:
Decidable Verification
Relational Abstraction
Three-Value Logic
Journal
P
IF:
2.8
Papers:
308
Citations:
4.7K
