36 research outputs found
Towards linking correctness conditions for concurrent objects and contextual trace refinement
Correctness conditions for concurrent objects describe how atomicity of an abstract sequential object may be decomposed. Many different concurrent objects and proof methods for them have been developed. However, arguments about correctness are conducted with respect to an object in isolation. This is in contrast to real-world practice, where concurrent objects are often implemented as part of a programming language library (e.g., java.util.concurrent) and are instantiated within a client program. A natural question to ask, then is: How does a correctness condition for a concurrent object ensure correctness of a client program that uses the concurrent object? This paper presents the main issues that surround this question and provides some answers by linking different correctness conditions with a form of trace refinement
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
LIPIcs
The semantics of concurrent data structures is usually given by a sequential specification and a consistency condition. Linearizability is the most popular consistency condition due to its simplicity and general applicability. Nevertheless, for applications that do not require all guarantees offered by linearizability, recent research has focused on improving performance and scalability of concurrent data structures by relaxing their semantics. In this paper, we present local linearizability, a relaxed consistency condition that is applicable to container-type concurrent data structures like pools, queues, and stacks. While linearizability requires that the effect of each operation is observed by all threads at the same time, local linearizability only requires that for each thread T, the effects of its local insertion operations and the effects of those removal operations that remove values inserted by T are observed by all threads at the same time. We investigate theoretical and practical properties of local linearizability and its relationship to many existing consistency conditions. We present a generic implementation method for locally linearizable data structures that uses existing linearizable data structures as building blocks. Our implementations show performance and scalability improvements over the original building blocks and outperform the fastest existing container-type implementations