We present SynVer — a novel, general purpose synthesizer for C programs equipped with machine-checked proofs of correctness using the Verified Software Toolchain. To do so, SynVer employs two Large Language Models (LLMs): the first generates candidate programs from user-provided specifications, and the second helps automatically construct formal proofs of their correctness in the Rocq proof assistant. To facilitate verification, SynVer places a set of syntactic restrictions on candidate programs that make them amenable to automated reasoning. SynVer uses a hybrid verification strategy that combines symbolic reasoning with LLM-powered proof generation to discharge proof obligations that the symbolic engine cannot handle on its own. We demonstrate the applicability of SynVer using a diverse set of benchmarks drawn from the program synthesis and verification literature.

Many interesting program properties involve the execution of multiple programs, including observational equivalence, noninterference, co-termination, monotonicity, and idempotency. One strategy for verifying such relational properties is to construct and reason about an intermediate program whose correctness implies that the individual programs exhibit those properties. A key challenge in building an intermediate program is finding a good alignment of the original programs. An alignment puts subparts of the original programs into correspondence so that their similarities can be exploited in order to simplify verification. We propose an approach to intermediate program construction that uses e-graphs, equality saturation, and algebraic realignment rules to efficiently represent and build programs amenable to automated verification. A key ingredient of our solution is a novel data-driven extraction technique that uses execution traces of candidate intermediate programs to identify solutions that are semantically well-aligned. We have implemented a relational verification engine based on our proposed approach, called KestRel , and use it to evaluate our approach over a suite of benchmarks taken from the relational verification literature.

Geo-replicated systems provide a number of desirable properties such as globally low latency, high availability, scalability, and built-in fault tolerance. Unfortunately, programming correct applications on top of such systems has proven to be very challenging, in large part because of the weak consistency guarantees they offer. These complexities are exacerbated when we try to adapt existing highly-performant concurrent libraries developed for shared-memory environments to this setting. The use of these libraries, developed with performance and scalability in mind, is highly desirable. But, identifying a suitable notion of correctness to check their validity under a weakly consistent execution model has not been well-studied, in large part because it is problematic to naïvely transplant criteria such as linearizability that has a useful interpretation in a shared-memory context to a distributed one where the cost of imposing a (logical) global ordering on all actions is prohibitive. In this paper, we tackle these issues by proposing appropriate semantics and specifications for highly-concurrent libraries in a weakly-consistent, replicated setting. We use these specifications to develop a static analysis framework that can automatically detect correctness violations of library implementations parameterized with respect to the different consistency policies provided by the underlying system. We use our framework to analyze the behavior of a number of highly non-trivial library implementations of stacks, queues, and exchangers. Our results provide the first demonstration that automated correctness checking of concurrent libraries in a weakly geo-replicated setting is both feasible and practical.