Linearizability with Ownership Transfer

Linearizability is a commonly accepted notion of correctness for libraries of concurrent algorithms. Unfortunately, it assumes a complete isolation between a library and its client, with interactions limited to passing values of a given data type. This is inappropriate for common programming languages, where libraries and their clients can communicate via the heap, transferring the ownership of data structures, and can even run in a shared address space without any memory protection. In this paper, we present the first definition of linearizability that lifts this limitation and establish an Abstraction Theorem: while proving a property of a client of a concurrent library, we can soundly replace the library by its abstract implementation related to the original one by our generalisation of linearizability. This allows abstracting from the details of the library implementation while reasoning about the client. We also prove that linearizability with ownership transfer can be derived from the classical one if the library does not access some of data structures transferred to it by the client

Concurrent Data Structures Linked in Time

Arguments about correctness of a concurrent data structure are typically carried out by using the notion of linearizability and specifying the linearization points of the data structure's procedures. Such arguments are often cumbersome as the linearization points' position in time can be dynamic (depend on the interference, run-time values and events from the past, or even future), non-local (appear in procedures other than the one considered), and whose position in the execution trace may only be determined after the considered procedure has already terminated. In this paper 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 name the idea linking-in-time, because it reduces temporal reasoning to spatial reasoning. For example, modifying a temporal position of a linearization point can be modeled similarly to a pointer update in separation logic. Furthermore, the auxiliary state provides a convenient way to concisely express the properties essential for reasoning about clients of such concurrent objects. We illustrate the method by verifying (mechanically in Coq) an intricate optimal snapshot algorithm due to Jayanti, as well as some clients

Specifying and Verifying Concurrent Algorithms with Histories and Subjectivity

We present a lightweight approach to Hoare-style specifications for fine-grained concurrency, based on a notion of time-stamped histories that abstractly capture atomic changes in the program state. Our key observation is that histories form a partial commutative monoid, a structure fundamental for representation of concurrent resources. This insight provides us with a unifying mechanism that allows us to treat histories just like heaps in separation logic. For example, both are subject to the same assertion logic and inference rules (e.g., the frame rule). Moreover, the notion of ownership transfer, which usually applies to heaps, has an equivalent in histories. It can be used to formally represent helping---an important design pattern for concurrent algorithms whereby one thread can execute code on behalf of another. Specifications in terms of histories naturally abstract granularity, in the sense that sophisticated fine-grained algorithms can be given the same specifications as their simplified coarse-grained counterparts, making them equally convenient for client-side reasoning. We illustrate our approach on a number of examples and validate all of them in Coq.Comment: 17 page

Defining correctness conditions for concurrent objects in multicore architectures

Correctness of concurrent objects is defined in terms of conditions that determine allowable relationships between histories of a concurrent object and those of the corresponding sequential object. Numerous correctness conditions have been proposed over the years, and more have been proposed recently as the algorithms implementing concurrent objects have been adapted to cope with multicore processors with relaxed memory architectures. We present a formal framework for defining correctness conditions for multicore architectures, covering both standard conditions for totally ordered memory and newer conditions for relaxed memory, which allows them to be expressed in uniform manner, simplifying comparison. Our framework distinguishes between order and commitment properties, which in turn enables a hierarchy of correctness conditions to be established. We consider the Total Store Order (TSO) memory model in detail, formalise known conditions for TSO using our framework, and develop sequentially consistent variations of these. We present a work-stealing deque for TSO memory that is not linearizable, but is correct with respect to these new conditions. Using our framework, we identify a new non-blocking compositional condition, fence consistency, which lies between known conditions for TSO, and aims to capture the intention of a programmer-specified fence

Hoare-style Specifications as Correctness Conditions for Non-linearizable Concurrent Objects

Designing scalable concurrent objects, which can be efficiently used on multicore processors, often requires one to abandon standard specification techniques, such as linearizability, in favor of more relaxed consistency requirements. However, the variety of alternative correctness conditions makes it difficult to choose which one to employ in a particular case, and to compose them when using objects whose behaviors are specified via different criteria. The lack of syntactic verification methods for most of these criteria poses challenges in their systematic adoption and application. In this paper, we argue for using Hoare-style program logics as an alternative and uniform approach for specification and compositional formal verification of safety properties for concurrent objects and their client programs. Through a series of case studies, we demonstrate how an existing program logic for concurrency can be employed off-the-shelf to capture important state and history invariants, allowing one to explicitly quantify over interference of environment threads and provide intuitive and expressive Hoare-style specifications for several non-linearizable concurrent objects that were previously specified only via dedicated correctness criteria. We illustrate the adequacy of our specifications by verifying a number of concurrent client scenarios, that make use of the previously specified concurrent objects, capturing the essence of such correctness conditions as concurrency-aware linearizability, quiescent, and quantitative quiescent consistency. All examples described in this paper are verified mechanically in Coq.Comment: 18 page

Steps in modular specifications for concurrent modules

© 2015 Published by Elsevier B.V.The specification of a concurrent program module is a difficult problem. The specifications must be strong enough to enable reasoning about the intended clients without reference to the underlying module implementation. We survey a range of verification techniques for specifying concurrent modules, in particular highlighting four key concepts: auxiliary state, interference abstraction, resource ownership and atomicity. We show how these concepts combine to provide powerful approaches to specifying concurrent modules

A Concurrent Perspective on Smart Contracts

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