Learning the boundary of inductive invariants
نویسندگان
چکیده
We study the complexity of invariant inference and its connections to exact concept learning. define a condition on invariants their geometry, called fence condition, which permits applying theoretical results from learning answer open problems in theory. The requires invariant's boundary---the states whose Hamming distance is one---to be backwards reachable bad small number steps. Using this we obtain first polynomial result for an interpolation-based algorithm, efficiently inferring monotone DNF with access SAT solver as oracle. further harness Bshouty's seminal infer larger syntactic class beyond DNF. Lastly, consider robustness under program transformations. show that some simple transformations preserve it sensitive more complex
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ژورنال
عنوان ژورنال: Proceedings of the ACM on programming languages
سال: 2021
ISSN: ['2475-1421']
DOI: https://doi.org/10.1145/3434296