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Éric Tanter

Publications and source records attributed to Éric Tanter.

At least 19 recordsLinked to original sources

Compiling Gradual Types with Evidence

Efficiently supporting sound gradual typing in a language with structural types is challenging. To date, the Grift compiler is the only close-to-the-metal implementation of gradual typing in this setting, exploiting coercions for runtime checks, and further extended with monotonic references for efficient access to statically-typed data structures. On the language design and semantics side, the Abstracting Gradual Typing (AGT) methodology has proven fruitful to elucidate existing designs and to innovate by deriving gradualizations of a wide variety of typing disciplines and language features. Grounded in abstract interpretation, the Curry-Howard inspired runtime semantics of AGT is based on the notion of evidence for consistent judgments that evolve during reduction, monitoring the plausibility of well-typedness. While expressive and versatile, it is unclear whether such evidence-based semantics are a viable route to realize an efficient implementation of gradual typing. In this work, we explore this question by designing, implementing, and evaluating an evidence-based compiler, called GrEv. We explain how to bridge the gap between the formal semantics and the GrEv compiler implementation, and identify novel monotonic semantics. We empirically evaluate the performance of GrEv on the Grift benchmark suite. The results show that an evidence-based compiler can be competitive with, and even faster than, a coercion-based compiler, exhibiting more stability across configurations on the static-to-dynamic spectrum. In addition to enriching the space of gradual typing compilers, this work opens a direct door to exploring efficient implementations of the many advanced gradual typing disciplines formally derived with AGT in the literature.

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Gradual Sensitivity Typing

Reasoning about the sensitivity of functions with respect to their inputs has interesting applications in various areas, such as differential privacy. In order to check and enforce sensitivity, several approaches have been developed, notably sensitivity type systems. In these systems, sensitivity can be seen as an effect in the sense of type-and-effects systems as originally proposed by Gifford and Lucassen. Because type-and-effect systems can make certain useful programming patterns tedious or overly conservative, there is value in bringing the benefits of gradual typing to these disciplines in order to ease their adoption. In this work, we motivate, formalize, and prototype gradual sensitivity typing. The language GSoul supports both the unrestricted unknown sensitivity and bounded imprecision in the form of intervals. Gradual sensitivity typing allows programmers to smoothly evolve typed programs without any static sensitivity information towards hardened programs with a mix of static and dynamic sensitivity checking. In particular, we show that gradual sensitivity supports recursive functions for which fully static checking would be overly conservative, seamlessly enabling exact runtime sensitivity checks. GSoul satisfies both the gradual guarantees and sensitivity type soundness, known as metric preservation. We establish that, in general, gradual metric preservation is termination insensitive, and that one can achieve termination-sensitive gradual metric preservation by hardening specifications to bounded imprecision. We implement a prototype that provides an interactive test bed for gradual sensitivity typing. This work opens the door to gradualizing other typing disciplines that rely on function sensitivity such as differential privacy, as well as other quantitative type-based reasoning techniques.

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Gradual C0: Symbolic Execution for Gradual Verification

Current static verification techniques support a wide range of programs. However, such techniques only support complete and detailed specifications, which places an undue burden on users. To solve this problem, prior work proposed gradual verification, which handles complete, partial, or missing specifications by soundly combining static and dynamic checking. Gradual verification has also been extended to programs that manipulate recursive, mutable data structures on the heap. Unfortunately, this extension does not reward users with decreased dynamic checking as specifications are refined. In fact, all properties are checked dynamically regardless of any static guarantees. Additionally, no full-fledged implementation of gradual verification exists so far, which prevents studying its performance and applicability in practice. We present Gradual C0, the first practicable gradual verifier for recursive heap data structures, which targets C0, a safe subset of C designed for education. Static verifiers supporting separation logic or implicit dynamic frames use symbolic execution for reasoning; so Gradual C0, which extends one such verifier, adopts symbolic execution at its core instead of the weakest liberal precondition approach used in prior work. Our approach addresses technical challenges related to symbolic execution with imprecise specifications, heap ownership, and branching in both program statements and specification formulas. We also deal with challenges related to minimizing insertion of dynamic checks and extensibility to other programming languages beyond C0. Finally, we provide the first empirical performance evaluation of a gradual verifier, and found that on average, Gradual C0 decreases run-time overhead between 11-34% compared to the fully-dynamic approach used in prior work. Further, the worst-case scenarios for performance are predictable and avoidable.

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Securing Verified IO Programs Against Unverified Code in F*

We introduce SCIO*, a formally secure compilation framework for statically verified partial programs performing input-output (IO). The source language is an F* subset in which a verified program interacts with its IO-performing context via a higher-order interface that includes refinement types as well as pre- and post-conditions about past IO events. The target language is a smaller F* subset in which the compiled program is linked with an adversarial context that has an interface without refinement types, pre-conditions, or concrete post-conditions. To bridge this interface gap and make compilation and linking secure we propose a formally verified combination of higher-order contracts and reference monitoring for recording and controlling IO operations. Compilation uses contracts to convert the logical assumptions the program makes about the context into dynamic checks on each context-program boundary crossing. These boundary checks can depend on information about past IO events stored in the state of the monitor. But these checks cannot stop the adversarial target context before it performs dangerous IO operations. Therefore linking in SCIO* additionally forces the context to perform all IO actions via a secure IO library, which uses reference monitoring to dynamically enforce an access control policy before each IO operation. We prove in F* that SCIO* soundly enforces a global trace property for the compiled verified program linked with the untrusted context. Moreover, we prove in F* that SCIO* satisfies by construction Robust Relational Hyperproperty Preservation, a very strong secure compilation criterion. Finally, we illustrate SCIO* at work on a simple web server example.

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Contextual Linear Types for Differential Privacy

Language support for differentially-private programming is both crucial and delicate. While elaborate program logics can be very expressive, type-system based approaches using linear types tend to be more lightweight and amenable to automatic checking and inference, and in particular in the presence of higher-order programming. Since the seminal design of Fuzz, which is restricted to $ε$-differential privacy in its original design, significant progress has been made to support more advancedvariants of differential privacy, like($ε$,$δ$)-differential privacy. However, supporting these advanced privacy variants while also supporting higher-order programming in full has proven to be challenging. We present Jazz, a language and type system which uses linear types and latent contextual effects to support both advanced variants of differential privacy and higher-order programming. Latent contextual effects allow delaying the payment of effects for connectives such as products, sums and functions, yielding advantages in terms of precision of the analysis and annotation burden upon elimination, as well as modularity. We formalize the core of Jazz, prove it sound for privacy via a logical relation for metric preservation, and illustrate its expressive power through a number of case studies drawn from the recent differential privacy literature.

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A Reasonably Gradual Type Theory

Gradualizing the Calculus of Inductive Constructions (CIC) involves dealing with subtle tensions between normalization, graduality, and conservativity with respect to CIC. Recently, GCIC has been proposed as a parametrized gradual type theory that admits three variants, each sacrificing one of these properties. For devising a gradual proof assistant based on CIC, normalization and conservativity with respect to CIC are key, but the tension with graduality needs to be addressed. Additionally, several challenges remain: (1) The presence of two wildcard terms at any type-the error and unknown terms-enables trivial proofs of any theorem, jeopardizing the use of a gradual type theory in a proof assistant; (2) Supporting general indexed inductive families, most prominently equality, is an open problem; (3) Theoretical accounts of gradual typing and graduality so far do not support handling type mismatches detected during reduction; (4) Precision and graduality are external notions not amenable to reasoning within a gradual type theory. All these issues manifest primally in CastCIC, the cast calculus used to define GCIC. In this work, we present an extension of CastCIC called GRIP. GRIP is a reasonably gradual type theory that addresses the issues above, featuring internal precision and general exception handling. GRIP features an impure (gradual) sort of types inhabited by errors and unknown terms, and a pure (non-gradual) sort of strict propositions for consistent reasoning about gradual terms. Internal precision supports reasoning about graduality within GRIP itself, for instance to characterize gradual exception-handling terms, and supports gradual subset types. We develop the metatheory of GRIP using a model formalized in Coq, and provide a prototype implementation of GRIP in Agda.

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Propositional Equality for Gradual Dependently Typed Programming

Gradual dependent types can help with the incremental adoption of dependently typed code by providing a principled semantics for imprecise types and proofs, where some parts have been omitted. Current theories of gradual dependent types, though, lack a central feature of type theory: propositional equality. Lennon-Bertrand et al. show that, when the reflexive proof $\mathit{refl}$ is the only closed value of an equality type, a gradual extension of CIC with propositional equality violates static observational equivalences. Extensionally-equal functions should be indistinguishable at run time, but the combination of equality and type imprecision allows for contexts that distinguish extensionally-equal but syntactically-different functions. This work presents a gradually typed language that supports propositional equality. We avoid the above issues by devising an equality type where $\mathit{refl}$ is not the only closed inhabitant. Instead, each equality proof carries a term that is at least as precise as the equated terms, acting as a witness of their plausible equality. These witnesses track partial type information as a program runs, raising errors when that information shows that two equated terms are undeniably inconsistent. Composition of type information is internalized as a construct of the language, and is deferred for function bodies whose evaluation is blocked by variables. By deferring, we ensure that extensionally equal functions compose without error, thereby preventing contexts from distinguishing them. We describe the challenges of designing consistency and precision relations for this system, along with solutions to these challenges. Finally, we prove important metatheory: type-safety, conservative embedding of CIC, canonicity, and the gradual guarantees of Siek et al.

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Gradualizing the Calculus of Inductive Constructions

We investigate gradual variations on the Calculus of Inductive Construction (CIC) for swifter prototyping with imprecise types and terms. We observe, with a no-go theorem, a crucial tradeoff between graduality and the key properties of normalization and closure of universes under dependent product that CIC enjoys. Beyond this Fire Triangle of Graduality, we explore the gradualization of CIC with three different compromises, each relaxing one edge of the Fire Triangle. We develop a parametrized presentation of Gradual CIC (GCIC) that encompasses all three variations, and develop their metatheory. We first present a bidirectional elaboration of GCIC to a dependently-typed cast calculus, CastCIC, which elucidates the interrelation between typing, conversion, and the gradual guarantees. We use a syntactic model of CastCIC to inform the design of a safe, confluent reduction, and establish, when applicable, normalization. We study the static and dynamic gradual guarantees as well as the stronger notion of graduality with embedding-projection pairs formulated by New and Ahmed, using appropriate semantic model constructions. This work informs and paves the way towards the development of malleable proof assistants and dependently-typed programming languages.

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The Multiverse: Logical Modularity for Proof Assistants

Proof assistants play a dual role as programming languages and logical systems. As programming languages, proof assistants offer standard modularity mechanisms such as first-class functions, type polymorphism and modules. As logical systems, however, modularity is lacking, and understandably so: incompatible reasoning principles -- such as univalence and uniqueness of identity proofs -- can indirectly lead to logical inconsistency when used in a given development, even when they appear to be confined to different modules. The lack of logical modularity in proof assistants also hinders the adoption of richer programming constructs, such as effects. We propose the multiverse, a general type-theoretic approach to endow proof assistants with logical modularity. The multiverse consists of multiple universe hierarchies that statically describe the reasoning principles and effects available to define a term at a given type. We identify sufficient conditions for this structuring to modularly ensure that incompatible principles do not interfere, and to locally restrict the power of dependent elimination when necessary. This extensible approach generalizes the ad-hoc treatment of the sort of propositions in the Coq proof assistant. We illustrate the power of the multiverse by describing the inclusion of Coq-style propositions, the strict propositions of Gilbert et al., the exceptional type theory of Pédrot and Tabareau, and general axiomatic extensions of the logic.

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Gradual Program Analysis for Null Pointers

Static analysis tools typically address the problem of excessive false positives by requiring programmers to explicitly annotate their code. However, when faced with incomplete annotations, many analysis tools are either too conservative, yielding false positives, or too optimistic, resulting in unsound analysis results. In order to flexibly and soundly deal with partially-annotated programs, we propose to build upon and adapt the gradual typing approach to abstract-interpretation-based program analyses. Specifically, we focus on null-pointer analysis and demonstrate that a gradual null-pointer analysis hits a sweet spot, by gracefully applying static analysis where possible and relying on dynamic checks where necessary for soundness. In addition to formalizing a gradual null-pointer analysis for a core imperative language, we build a prototype using the Infer static analysis framework, and present preliminary evidence that the gradual null-pointer analysis reduces false positives compared to two existing null-pointer checkers for Infer. Further, we discuss ways in which the gradualization approach used to derive the gradual analysis from its static counterpart can be extended to support more domains. This work thus provides a basis for future analysis tools that can smoothly navigate the tradeoff between human effort and run-time overhead to reduce the number of reported false positives.

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Approximate Normalization and Eager Equality Checking for Gradual Inductive Families

Harnessing the power of dependently typed languages can be difficult. Programmers must manually construct proofs to produce well-typed programs, which is not an easy task. In particular, migrating code to these languages is challenging. Gradual typing can make dependently-typed languages easier to use by mixing static and dynamic checking in a principled way. With gradual types, programmers can incrementally migrate code to a dependently typed language. However, adding gradual types to dependent types creates a new challenge: mixing decidable type-checking and incremental migration in a full-featured language is a precarious balance. Programmers expect type-checking to terminate, but dependent type-checkers evaluate terms at compile time, which is problematic because gradual types can introduce non-termination into an otherwise terminating language. Steps taken to mitigate this non-termination must not jeopardize the smooth transitions between dynamic and static. We present a gradual dependently-typed language that supports inductive type families, has decidable type-checking, and provably supports smooth migration between static and dynamic, as codified by the refined criteria for gradual typing proposed by Siek et al. (2015). Like Eremondi et al. (2019), we use approximate normalization for terminating compile-time evaluation. Unlike Eremondi et al., our normalization does not require comparison of variables, allowing us to show termination with a syntactic model that accommodates inductive types. Moreover, we design a novel a technique for tracking constraints on type indices, so that dynamic constraint violations signal run-time errors eagerly. To facilitate these checks, we define an algebraic notion of gradual precision, axiomatizing certain semantic properties of gradual terms.

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The Marriage of Univalence and Parametricity

Reasoning modulo equivalences is natural for everyone, including mathematicians. Unfortunately, in proof assistants based on type theory, equality is appallingly syntactic and, as a result, exploiting equivalences is cumbersome at best. Parametricity and univalence are two major concepts that have been explored to transport programs and proofs across type equivalences, but they fall short of achieving seamless, automatic transport. This work first clarifies the limitations of these two concepts in isolation, and then devises a fruitful marriage between both. The resulting concept, univalent parametricity, is an heterogeneous extension of parametricity strengthened with univalence that fully realizes programming and proving modulo equivalences. In addition to the theory of univalent parametricity, we present a lightweight framework implemented in Coq that allows the user to transparently transfer definitions and theorems for a type to an equivalent one, as if they were equal. For instance, this makes it possible to conveniently switch between an easy-to-reason-about representation and a computationally-efficient representation, as soon as they are proven equivalent. The combination of parametricity and univalence supports transport à la carte: basic univalent transport, which stems from a type equivalence, can be complemented with additional proofs of equivalences between functions over these types, in order to be able to lift more programs and proofs, as well as to yield more efficient terms. We illustrate the use of univalent parametricity on several examples, including a recent integration of native integers in Coq.

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Gradual System F

Bringing the benefits of gradual typing to a language with parametric polymorphism like System F, while preserving relational parametricity, has proven extremely challenging: first attempts were formulated a decade ago, and several designs have been recently proposed, with varying syntax, behavior, and properties. Starting from a detailed review of the challenges and tensions that affect the design of gradual parametric languages, this work presents an extensive account of the semantics and metatheory of GSF, a gradual counterpart of System F. In doing so, we also report on the extent to which the Abstracting Gradual Typing methodology can help us derive such a language. Among gradual parametric languages that follow the syntax of System F, GSF achieves a unique combination of properties. We clearly establish the benefits and limitations of the language, and discuss several extensions of GSF towards a practical programming language.

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Trace-Relating Compiler Correctness and Secure Compilation

Compiler correctness is, in its simplest form, defined as the inclusion of the set of traces of the compiled program into the set of traces of the original program, which is equivalent to the preservation of all trace properties. Here traces collect, for instance, the externally observable events of each execution. This definition requires, however, the set of traces of the source and target languages to be exactly the same, which is not the case when the languages are far apart or when observations are fine-grained. To overcome this issue, we study a generalized compiler correctness definition, which uses source and target traces drawn from potentially different sets and connected by an arbitrary relation. We set out to understand what guarantees this generalized compiler correctness definition gives us when instantiated with a non-trivial relation on traces. When this trace relation is not equality, it is no longer possible to preserve the trace properties of the source program unchanged. Instead, we provide a generic characterization of the target trace property ensured by correctly compiling a program that satisfies a given source property, and dually, of the source trace property one is required to show in order to obtain a certain target property for the compiled code. We show that this view on compiler correctness can naturally account for undefined behavior, resource exhaustion, different source and target values, side-channels, and various abstraction mismatches. Finally, we show that the same generalization also applies to many secure compilation definitions, which characterize the protection of a compiled program against linked adversarial code.

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Existential Types for Relaxed Noninterference

Information-flow security type systems ensure confidentiality by enforcing noninterference: a program cannot leak private data to public channels. However, in practice, programs need to selectively declassify information about private data. Several approaches have provided a notion of relaxed noninterference supporting selective and expressive declassification while retaining a formal security property. The labels-as-functions approach provides relaxed noninterference by means of declassification policies expressed as functions. The labels-as-types approach expresses declassification policies using type abstraction and faceted types, a pair of types representing the secret and public facets of values. The original proposal of labels-as-types is formulated in an object-oriented setting where type abstraction is realized by subtyping. The object-oriented approach however suffers from limitations due to its receiver-centric paradigm. In this work, we consider an alternative approach to labels-as-types, applicable in non-object-oriented languages, which allows us to express advanced declassification policies, such as extrinsic policies, based on a different form of type abstraction: existential types. An existential type exposes abstract types and operations on these; we leverage this abstraction mechanism to express secrets that can be declassified using the provided operations. We formalize the approach in a core functional calculus with existential types, define existential relaxed noninterference, and prove that well-typed programs satisfy this form of type-based relaxed noninterference.

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Gradual Liquid Type Inference

Liquid typing provides a decidable refinement inference mechanism that is convenient but subject to two major issues: (1) inference is global and requires top-level annotations, making it unsuitable for inference of modular code components and prohibiting its applicability to library code, and (2) inference failure results in obscure error messages. These difficulties seriously hamper the migration of existing code to use refinements. This paper shows that gradual liquid type inference---a novel combination of liquid inference and gradual refinement types---addresses both issues. Gradual refinement types, which support imprecise predicates that are optimistically interpreted, can be used in argument positions to constrain liquid inference so that the global inference process e effectively infers modular specifications usable for library components. Dually, when gradual refinements appear as the result of inference, they signal an inconsistency in the use of static refinements. Because liquid refinements are drawn from a nite set of predicates, in gradual liquid type inference we can enumerate the safe concretizations of each imprecise refinement, i.e. the static refinements that justify why a program is gradually well-typed. This enumeration is useful for static liquid type error explanation, since the safe concretizations exhibit all the potential inconsistencies that lead to static type errors. We develop the theory of gradual liquid type inference and explore its pragmatics in the setting of Liquid Haskell.

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Polymorphic Relaxed Noninterference

Information-flow security typing statically preserves confidentiality by enforcing noninterference. To address the practical need of selective and flexible declassification of confidential information, several approaches have developed a notion of relaxed noninterference, where security labels are either functions or types. The labels-as-types approach to relaxed noninterference supports expressive declassification policies, including recursive ones, via a simple subtyping-based ordering, and provides a local, modular reasoning principle. In this work, we extend this expressive declassification approach in order to support polymorphic declassification. First, we identify the need for bounded polymorphism through concrete examples. We then formalize polymorphic relaxed noninterference in a typed object-oriented calculus, using a step-indexed logical relation to prove that all well-typed terms are secure. Finally, we address the case of primitive types, which requires a form of ad-hoc polymorphism. Therefore, this work addresses practical hurdles to providing controlled and expressive declassification for the construction of information-flow secure systems.

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Approximate Normalization for Gradual Dependent Types

Dependent types help programmers write highly reliable code. However, this reliability comes at a cost: it can be challenging to write new prototypes in (or migrate old code to) dependently-typed programming languages. Gradual typing makes static type disciplines more flexible, so an appropriate notion of gradual dependent types could fruitfully lower this cost. However, dependent types raise unique challenges for gradual typing. Dependent typechecking involves the execution of program code, but gradually-typed code can signal runtime type errors or diverge. These runtime errors threaten the soundness guarantees that make dependent types so attractive, while divergence spoils the type-driven programming experience. This paper presents GDTL, a gradual dependently-typed language that emphasizes pragmatic dependently-typed programming. GDTL fully embeds both an untyped and dependently-typed language, and allows for smooth transitions between the two. In addition to gradual types we introduce gradual terms , which allow the user to be imprecise in type indices and to omit proof terms; runtime checks ensure type safety . To account for nontermination and failure, we distinguish between compile-time normalization and run-time execution: compile-time normalization is approximate but total, while runtime execution is exact , but may fail or diverge. We prove that GDTL has decidable typechecking and satisfies all the expected properties of gradual languages. In particular, GDTL satisfies the static and dynamic gradual guarantees: reducing type precision preserves typedness, and altering type precision does not change program behavior outside of dynamic type failures. To prove these properties, we were led to establish a novel normalization gradual guarantee that captures the monotonicity of approximate normalization with respect to imprecision.

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