Growing a Proof Assistant.
William J. Bowman.
Sophisticated domain-specific and user-defined notation is widely used in formal models, but is poorly supported by proof assistants. Many proof assistants support simple notation definitions, but no proof assistant enables users to conveniently define sophisticated notation. For instance, in modeling a programming language, we often define infix relations such as Γ ⊢ e : t and use BNF notation to specify the syntax of the language. In a proof assistant like Coq or Agda, users can easily define the notation for Γ ⊢ e : t, but to use BNF notation the user must use a preprocessing tool external to the proof assistant, which is cumbersome.
To support sophisticated user-defined notation, we propose to use language extension as a fundamental part of the design of a proof assistant. We describe how to design a language-extension systems that support safe, convenient, and sophisticated user-defined extensions, and how to design a proof assistant based on language extension. We evaluate this design by building a proof assistant that features a small dependent type theory as the core language and implementing the following extensions in small user-defined libraries: pattern matching for inductive types, dependently-typed staged meta-programming, a tactic-based proof language, and BNF and inference-rule notation for inductive type definitions.Abstract | PDF ((Very preliminary) draft as of Apr 20, 2017) | HOPE 2016 Presentation GitHub
Fully Abstract Compilation via Universal Embedding.
Max New, William J. Bowman, Amal Ahmed.
To appear in Proc. of the 21st International Conference on Functional Programming (ICFP 2016)
A fully abstract compiler guarantees that two source components are observationally equivalent in the source language if and only if their translations are observationally equivalent in the target. Full abstraction implies the translation is secure: target-language attackers can make no more observations of a compiled component than a source-language attacker interacting with the original source component. Proving full abstraction for realistic compilers is challenging because realistic target languages contain features (such as control effects) unavailable in the source, while proofs of full abstraction require showing that every target context to which a compiled component may be linked can be back-translated to a behaviorally equivalent source context.
We prove the first full abstraction result for a translation whose target language contains exceptions, but the source does not. Our translation—
Noninterference for Free.
William J. Bowman, Amal Ahmed.
In Proc. of the 20th International Conference on Functional Programming (ICFP 2015)
Abadi et. al. (1999) introduced the dependency core calculus (DCC) as a framework for studying a variety of dependency analyses (e.g., secure information flow). The key property provided by DCC is noninterference, which guarantees that a low-level observer (attacker) cannot distinguish high-level (protected) computations. The proof of noninterference for DCC suggests a connection to parametricity in System F, which suggests that it should be possible to implement dependency analyses in languages with parametric polymorphism.
In this paper, we present a translation from DCC into Fω and prove that the translation preserves noninterference. To express noninterference in Fω we define a notion of observer-sensitive equivalence that makes essential use of both first-order and higher-order polymorphism. Our translation provides insights into DCC’s type system and shows how DCC can be implemented in a polymorphic language without loss of the security/noninterference guarantees available in DCC. Our contributions include proof techniques that should be valuable when proving other secure compilation or full abstraction results.Abstract | PDF (Author-Izer) | PDF (Preprint) | Technical Appendix (Draft) | ICFP 2015 Presentation
William J. Bowman, Swaha Miller, Vincent St-Amour, and R. Kent Dybvig.
In Proc. of the 36th Conference on Programming Language Implementation and Design (PLDI 2015).
Contemporary compiler systems such as GCC, .NET, and LLVM incorporate profile-guided optimizations (PGOs) on low-level intermediate code and basic blocks, with impressive results over purely static heuristics. Recent work shows that profile information is also useful for performing source-to-source optimizations via meta-programming. For example, using profiling information to inform decisions about data structures and algorithms can potentially lead to asymptotic improvements in performance.
We present a design for profile-guided meta-programming in a general-purpose meta-programming system. Our design is parametric over the particular profiler and meta-programming system. We implement this design in two different meta-programming systems—