Faithful Autoformalization of Natural Language Assertions
Formal contracts are essential for software testing and verification, yet writing them remains labor-intensive and error-prone. LLMs offer a promising path toward autoformalization: synthesizing executable assertions from natural-language specifications and thereby bridging the gap between informal developer intent and formal executable specifications. We present Monty: an autoformalization framework for assertions that tackles the challenges of expectations of validity of assertions and ambiguity in natural-language. Our techniques are based on filtering formalizations using a novel conformance score metric and validity scores obtained from testing the code against formalized assertions....
| Authors | Hongyi Liu, Madhusudan Parthasarathy, Adithya Murali |
|---|---|
| Primary category | cs.SE |
| Published | 14 July 2026 |
| Last updated at source | 16 July 2026 |
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