paperbot · PL 论文追踪

RSS

Scaling Instruction-Selection Verification against Authoritative ISA Semantics

OOPSLA 9(OOPSLA2)2025
Michael McLoughlin, Ashley Sheng, Chris Fallin, Bryan Parno, Fraser Brown, Alexa VanHattum

尚未生成 AI 速览(可能缺少 API key 或等待下次运行补跑)。

原文摘要(Abstract)

Secure, performant execution of untrusted code—as promised by WebAssembly (Wasm)—requires correct compilation to native code that enforces a sandbox. Errors in instruction selection can undermine the sandbox’s guarantees, but prior verification work struggles to scale to the complexity of realistic industrial compilers. We present Arrival , an instruction-selection verifier for the Cranelift production Wasm-to-native compiler. Arrival enables end-to-end, high-assurance verification while reducing developer effort. Arrival ( 1 ) automatically reasons about chains of instruction-selection rules, thereby reducing the need for develop-er-supplied intermediate specifications, ( 2 ) introduces a lightweight, efficient method for reasoning about stateful instruction-selection rules, and ( 3 ) automatically derives high-assurance machine code specifications. Our work verifies nearly all AArch64 instruction-selection rules reachable from Wasm core. Furthermore, Arrival reduces the developer effort required: 60 % of all specifications benefit from our automation, thereby requiring 2.6 × fewer hand-written specifications than prior approaches. Arrival finds new bugs in Cranelift’s instruction selection, and it is viable for integration into production workflows.

链接与引用

DOI 原文 ·

BibTeX
@article{paperbot2893,
  title = {Scaling Instruction-Selection Verification against Authoritative ISA Semantics},
  author = {Michael McLoughlin and Ashley Sheng and Chris Fallin and Bryan Parno and Fraser Brown and Alexa VanHattum},
  journal = {Proceedings of the ACM on Programming Languages},
  volume = {9},
  number = {OOPSLA2},
  year = {2025},
  doi = {10.1145/3764383}
}