15 research outputs found

    Communicating State Transition Systems for Fine-Grained Concurrent Resources

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    Concurrent Data Structures Linked in Time (Artifact)

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    This artifact provides the full mechanization in FCSL of the developments in the companion paper, "Concurrent Data Structures Linked in Time". In the latter, we propose a new method, based on a separation-style logic, for reasoning about concurrent objects with such linearization points. We embrace the dynamic nature of linearization points, and encode it as part of the data structure's auxiliary state, so that it can be dynamically modified in place by auxiliary code, as needed when some appropriate run-time event occurs. We illustrate the method by verifying (mechanically in FCSL) an intricate optimal snapshot algorithm due to Jayanti, as well as some clients. FCSL is the first completely formalized framework for mechanized verification of full functional correctness of fine-grained concurrent programs. It is implemented as an embedded domain-specific language (DSL) in the dependently-typed language of the Coq proof assistant, and is powerful enough to reason about programming features such as higher-order functions and local thread spawning. By incorporating a uniform concurrency model, based on state-transition systems and partial commutative monoids, FCSL makes it possible to build proofs about concurrent libraries in a thread-local, compositional way, thus facilitating scalability and reuse: libraries are verified just once, and their specifications are used ubiquitously in client-side reasoning

    A Concurrent Perspective on Smart Contracts

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    In this paper, we explore remarkable similarities between multi-transactional behaviors of smart contracts in cryptocurrencies such as Ethereum and classical problems of shared-memory concurrency. We examine two real-world examples from the Ethereum blockchain and analyzing how they are vulnerable to bugs that are closely reminiscent to those that often occur in traditional concurrent programs. We then elaborate on the relation between observable contract behaviors and well-studied concurrency topics, such as atomicity, interference, synchronization, and resource ownership. The described contracts-as-concurrent-objects analogy provides deeper understanding of potential threats for smart contracts, indicate better engineering practices, and enable applications of existing state-of-the-art formal verification techniques.Comment: 15 page

    IST Austria Technical Report

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    Synchronous programs are easy to specify because the side effects of an operation are finished by the time the invocation of the operation returns to the caller. Asynchronous programs, on the other hand, are difficult to specify because there are side effects due to pending computation scheduled as a result of the invocation of an operation. They are also difficult to verify because of the large number of possible interleavings of concurrent asynchronous computation threads. We show that specifications and correctness proofs for asynchronous programs can be structured by introducing the fiction, for proof purposes, that intermediate, non-quiescent states of asynchronous operations can be ignored. Then, the task of specification becomes relatively simple and the task of verification can be naturally decomposed into smaller sub-tasks. The sub-tasks iteratively summarize, guided by the structure of an asynchronous program, the atomic effect of non-atomic operations and the synchronous effect of asynchronous operations. This structuring of specifications and proofs corresponds to the introduction of multiple layers of stepwise refinement for asynchronous programs. We present the first proof rule, called synchronization, to reduce asynchronous invocations on a lower layer to synchronous invocations on a higher layer. We implemented our proof method in CIVL and evaluated it on a collection of benchmark programs

    Programming and Proving with Distributed Protocols

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    Distributed systems play a crucial role in modern infrastructure, but are notoriously difficult to implement correctly. This difficulty arises from two main challenges: (a) correctly implementing core system components (e.g., two-phase commit), so all their internal invariants hold, and (b) correctly composing standalone system components into functioning trustworthy applications (e.g., persistent storage built on top of a two-phase commit instance). Recent work has developed several approaches for addressing (a) by means of mechanically verifying implementations of core distributed components, but no methodology exists to address (b) by composing such verified components into larger verified applications. As a result, expensive verification efforts for key system components are not easily reusable, which hinders further verification efforts. In this paper, we present Disel, the first framework for implementation and compositional verification of distributed systems and their clients, all within the mechanized, foundational context of the Coq proof assistant. In Disel, users implement distributed systems using a domain specific language shallowly embedded in Coq and providing both high-level programming constructs as well as low-level communication primitives. Components of composite systems are specified in Disel as protocols, which capture system-specific logic and disentangle system definitions from implementation details. By virtue of Disel’s dependent type system, well-typed implementations always satisfy their protocols’ invariants and never go wrong, allowing users to verify system implementations interactively using Disel’s Hoare-style program logic, which extends state-of-the-art techniques for concurrency verification to the distributed setting. By virtue of the substitution principle and frame rule provided by Disel’s logic, system components can be composed leading to modular, reusable verified distributed systems. We describe Disel, illustrate its use with a series of examples, outline its logic and metatheory, and report on our experience using it as a framework for implementing, specifying, and verifying distributed systems
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