Relational program logics are a popular formalism for stating and proving properties that relate executions of several computations. We present Infinitary Relational Logic (IRL)—the first Hoare-style Separation Logic that allows one to state and prove relational properties of possibly infinite families of arbitrary programs. The key insights behind IRL are to (a) generalise relational program specifications in the style of Separation Logic triples to families of programs indexed by arbitrary infinite sets, and (b) provide general proof rules that support reasoning principles guided by the structure of these index sets.

We have implemented IRL as a foundational embedding and verification tool on top of the Lean proof assistant. We demonstrate its power by showcasing both the practical and theoretical advances IRL brings to the state of the art in deductive program verification. To show the former, we use IRL to specify and prove the correctness of a series of previously unverified algorithms from computer graphics and geo-spatial information systems that iterate over array-encoded continuous objects. In doing so, we show that specifying representations of implicitly continuous data using code rather than traditional state invariants offers pragmatic benefits in the form of concise and reusable proofs, while retaining full compatibility with conventional non-relational Hoare-style reasoning. To show the latter, we use IRL to specify and verify a novel notion we call Weird Machine Realisability, providing the first conceptual framework that formally characterises the space of unintended behaviours permitted by a vulnerable program. All our case studies are formalised in Lean.