{DistAI}:{Data-Driven} automated invariant learning for distributed protocols

J Yao, R Tao, R Gu, J Nieh, S Jana… - 15th USENIX symposium …, 2021 - usenix.org
Distributed systems are notoriously hard to implement correctly due to non-determinism.
Finding the inductive invariant of the distributed protocol is a critical step in verifying the …

{DuoAI}: Fast, automated inference of inductive invariants for verifying distributed protocols

J Yao, R Tao, R Gu, J Nieh - 16th USENIX Symposium on Operating …, 2022 - usenix.org
Distributed systems are complex and difficult to build correctly. Formal verification can
provably rule out bugs in such systems, but finding an inductive invariant that implies the …

Semantic code refactoring for abstract data types

S Pailoor, Y Wang, I Dillig - Proceedings of the ACM on Programming …, 2024 - dl.acm.org
Modifications to the data representation of an abstract data type (ADT) can require
significant semantic refactoring of the code. Motivated by this observation, this paper …

Program sketching with live bidirectional evaluation

J Lubin, N Collins, C Omar, R Chugh - Proceedings of the ACM on …, 2020 - dl.acm.org
We present a system called Smyth for program sketching in a typed functional language
whereby the concrete evaluation of ordinary assertions gives rise to input-output examples …

Recursion synthesis with unrealizability witnesses

A Farzan, D Lette, V Nicolet - Proceedings of the 43rd ACM SIGPLAN …, 2022 - dl.acm.org
We propose SE2GIS, a novel inductive recursion synthesis approach with the ability to both
synthesize code and declare a problem unsolvable. SE2GIS combines a symbolic variant of …

Leveraging large language models for automated proof synthesis in rust

J Yao, Z Zhou, W Chen, W Cui - arXiv preprint arXiv:2311.03739, 2023 - arxiv.org
Formal verification can provably guarantee the correctness of critical system software, but
the high proof burden has long hindered its wide adoption. Recently, Large Language …

Almost correct invariants: Synthesizing inductive invariants by fuzzing proofs

S Lahiri, S Roy - Proceedings of the 31st ACM SIGSOFT International …, 2022 - dl.acm.org
Real-life programs contain multiple operations whose semantics are unavailable to
verification engines, like third-party library calls, inline assembly and SIMD instructions …

Induction duality: primal-dual search for invariants

O Padon, JR Wilcox, JR Koenig, KL McMillan… - Proceedings of the …, 2022 - dl.acm.org
Many invariant inference techniques reason simultaneously about states and predicates,
and it is well-known that these two kinds of reasoning are in some sense dual to each other …

The SemGuS Toolkit

KJC Johnson, A Reynolds, T Reps… - … Conference on Computer …, 2024 - Springer
Abstract Semantics-Guided Synthesis (SemGuS) is a programmable framework for defining
synthesis problems in a domain-and solver-agnostic way. This paper presents the …

Data-driven invariant learning for probabilistic programs

J Bao, N Trivedi, D Pathak, J Hsu, S Roy - Formal Methods in System …, 2024 - Springer
Morgan and McIver's weakest pre-expectation framework is one of the most well-established
methods for deductive verification of probabilistic programs. Roughly, the idea is to …