Self-Supervised Learning to Prove Equivalence Between Programs via Semantics-Preserving Rewrite Rules. (arXiv:2109.10476v2 [cs.LG] UPDATED)

We target the problem of automatically synthesizing proofs of semantic
equivalence between two programs made of sequences of statements. We represent
programs using abstract syntax trees (AST), where a given set of
semantics-preserving rewrite rules can be applied on a specific AST pattern to
generate a transformed and semantically equivalent program. In our system, two
programs are equivalent if there exists a sequence of application of these
rewrite rules that leads to rewriting one program into the other. We propose …

arxiv learning rules self-supervised learning supervised learning