The specifications of mainstream processor architectures, such as Arm, x86, and RISC-V, underlie modern computing, as the targets of compilers, operating systems, and hypervisors. However, despite extensive research and tooling for instruction-set architecture (ISA) and relaxed-memory semantics, recently including systems features, there still do not exist integrated mathematical models that suffice for foundational formal verification, of concurrent architecture properties or of systems software. Previous proof-assistant work has had to substantially simplify the ISA semantics, the concurrency model, or both. We present ArchSem, an architecture-generic framework for architecture semantics, modularly combining ISA and concurrency models along a tractable interface of instruction-semantics effects, that covers a range of systems aspects. To do so, one has to handle many issues that were previously unclear, about the architectures themselves, the interface, the proper definition of reusable models, and the Rocq and Isabelle idioms required to make it usable. We instantiate it to the Arm-A and RISC-V instruction-set architectures and multiple concurrency models. We demonstrate usability for proof, despite the scale, by establishing that the Arm architecture (in a particular configuration) provides a provable virtual memory abstraction, with a combination of Rocq, Isabelle, and paper proof. Previous work provides further confirmation of usability: the AxSL program logic for Arm relaxed concurrency was proved sound above an earlier version of ArchSem. This establishes a basis for future proofs of architecture properties and systems software, above production architecture specifications.

@article{paperbot3937,
  title = {ArchSem: Reusable Rigorous Semantics of Relaxed Architectures},
  author = {Thibaut Pérami and Thomas Bauereiss and Brian Campbell and Zongyuan Liu and Nils Lauermann and Alasdair Armstrong and Peter Sewell},
  journal = {Proceedings of the ACM on Programming Languages},
  volume = {10},
  number = {POPL},
  year = {2026},
  doi = {10.1145/3776650}
}