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Cezar-Constantin Andrici

Publications and source records attributed to Cezar-Constantin Andrici.

5 recordsLinked to original sources
arXiv2026

Misquoted No More: Securely Extracting F* Programs with IO

Shallow embeddings that use monads to represent effects are popular in proof-oriented languages because they are convenient for formal verification. Once shallowly embedded programs are verified, they are often extracted to mainstream languages like OCaml or C and linked into larger codebases. The extraction process is not fully verified because it often involves quotation -- turning the shallowly embedded program into a deeply embedded one -- and verifying quotation remains a major open challenge. Instead, some prior work obtains formal correctness guarantees using translation validation to certify individual extraction results. We build on this idea, but limit the use of translation validation to a first extraction step that we call relational quotation and that uses a metaprogram to construct a typing derivation for the given shallowly embedded program. This metaprogram is simple, since the typing derivation follows the structure of the original program. Once we validate that the typing derivation is valid for the original program, we pass it to a verified syntax-generation function that produces code guaranteed to be semantically related to the original program. We apply this general idea to build SEIO*, a framework for extracting shallowly embedded F* programs with IO and refinement types to a deeply embedded simply typed lambda-calculus while providing formal secure compilation guarantees. Using two cross-language logical relations, we devise a machine-checked proof in F* that SEIO* guarantees Robust Relational Hyperproperty Preservation (RrHP), a very strong secure compilation criterion that implies full abstraction as well as preservation of trace properties and hyperproperties against arbitrary linked adversarial code. This goes beyond the state of the art in verified and certifying extraction, which so far has focused on correctness rather than security.

cs.PL↗
arXiv2025

SecRef*: Securely Sharing Mutable References Between Verified and Unverified Code in F*

We introduce SecRef*, a secure compilation framework protecting stateful programs verified in F* against linked unverified code, with which the program dynamically shares ML-style mutable references. To ease program verification in this setting, we propose a way of tracking which references are shareable with the unverified code, and which ones are not shareable and whose contents are thus guaranteed to be unchanged after calling into unverified code. This universal property of non-shareable references is exposed in the interface on which the verified program can rely when calling into unverified code. The remaining refinement types and pre- and post-conditions that the verified code expects from the unverified code are converted into dynamic checks about the shared references by using higher-order contracts. We prove formally in F* that this strategy ensures sound and secure interoperability with unverified code. Since SecRef* is built on top of the Monotonic State effect of F*, these proofs rely on the first monadic representation for this effect, which is a contribution of our work that can be of independent interest. Finally, we use SecRef* to build a simple cooperative multi-threading scheduler that is verified and that securely interacts with unverified threads.

cs.PL↗
arXiv2023

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.

cs.PL↗
arXiv2020

Who Verifies the Verifiers? A Computer-Checked Implementation of the DPLL Algorithm in Dafny

We build a SAT solver implementing the DPLL algorithm in the verification-enabled programming language Dafny. The resulting solver is fully verified (soundness, completeness and termination are computer checked). We benchmark our Dafny solver and we show that it is just as efficient as an equivalent DPLL solver implemented in C# and roughly two times less efficient than an equivalent solver written in C++. We conclude that auto-active verification is a promising approach to increasing trust in SAT solvers, as it combines a good trade-off between execution speed and degree of trustworthiness of the final product.

cs.LO↗
arXiv2019

Verifying the DPLL Algorithm in Dafny

Modern high-performance SAT solvers quickly solve large satisfiability instances that occur in practice. If the instance is satisfiable, then the SAT solver can provide a witness which can be checked independently in the form of a satisfying truth assignment. However, if the instance is unsatisfiable, the certificates could be exponentially large or the SAT solver might not be able to output certificates. The implementation of the SAT solver should then be trusted not to contain bugs. However, the data structures and algorithms implemented by a typical high-performance SAT solver are complex enough to allow for subtle programming errors. To counter this issue, we build a verified SAT solver using the Dafny system. We discuss its implementation in the present article.

cs.LO↗