21 research outputs found
On Verifying Causal Consistency
Causal consistency is one of the most adopted consistency criteria for
distributed implementations of data structures. It ensures that operations are
executed at all sites according to their causal precedence. We address the
issue of verifying automatically whether the executions of an implementation of
a data structure are causally consistent. We consider two problems: (1)
checking whether one single execution is causally consistent, which is relevant
for developing testing and bug finding algorithms, and (2) verifying whether
all the executions of an implementation are causally consistent.
We show that the first problem is NP-complete. This holds even for the
read-write memory abstraction, which is a building block of many modern
distributed systems. Indeed, such systems often store data in key-value stores,
which are instances of the read-write memory abstraction. Moreover, we prove
that, surprisingly, the second problem is undecidable, and again this holds
even for the read-write memory abstraction. However, we show that for the
read-write memory abstraction, these negative results can be circumvented if
the implementations are data independent, i.e., their behaviors do not depend
on the data values that are written or read at each moment, which is a
realistic assumption.Comment: extended version of POPL 201
Polynomial-Time Verification and Testing of Implementations of the Snapshot Data Structure
We analyze correctness of implementations of the snapshot data structure in terms of linearizability. We show that such implementations can be verified in polynomial time. Additionally, we identify a set of representative executions for testing and show that the correctness of each of these executions can be validated in linear time. These results present a significant speedup considering that verifying linearizability of implementations of concurrent data structures, in general, is EXPSPACE-complete in the number of program-states, and testing linearizability is NP-complete in the length of the tested execution. The crux of our approach is identifying a class of executions, which we call simple, such that a snapshot implementation is linearizable if and only if all of its simple executions are linearizable. We then divide all possible non-linearizable simple executions into three categories and construct a small automaton that recognizes each category. We describe two implementations (one for verification and one for testing) of an automata-based approach that we develop based on this result and an evaluation that demonstrates significant improvements over existing tools. For verification, we show that restricting a state-of-the-art tool to analyzing only simple executions saves resources and allows the analysis of more complex cases. Specifically, restricting attention to simple executions finds bugs in 27 instances, whereas, without this restriction, we were only able to find 14 of the 30 bugs in the instances we examined. We also show that our technique accelerates testing performance significantly. Specifically, our implementation solves the complete set of 900 problems we generated, whereas the state-of-the-art linearizability testing tool solves only 554 problems
Checking Linearizability of Concurrent Priority Queues
Efficient implementations of concurrent objects such as atomic collections
are essential to modern computing. Programming such objects is error prone: in
minimizing the synchronization overhead between concurrent object invocations,
one risks the conformance to sequential specifications -- or in formal terms,
one risks violating linearizability. Unfortunately, verifying linearizability
is undecidable in general, even on classes of implementations where the usual
control-state reachability is decidable. In this work we consider concurrent
priority queues which are fundamental to many multi-threaded applications such
as task scheduling or discrete event simulation, and show that verifying
linearizability of such implementations can be reduced to control-state
reachability. This reduction entails the first decidability results for
verifying concurrent priority queues in the context of an unbounded number of
threads, and it enables the application of existing safety-verification tools
for establishing their correctness.Comment: An extended abstract is published in the Proceedings of CONCUR 201
Faster linearizability checking via -compositionality
Linearizability is a well-established consistency and correctness criterion
for concurrent data types. An important feature of linearizability is Herlihy
and Wing's locality principle, which says that a concurrent system is
linearizable if and only if all of its constituent parts (so-called objects)
are linearizable. This paper presents -compositionality, which generalizes
the idea behind the locality principle to operations on the same concurrent
data type. We implement -compositionality in a novel linearizability
checker. Our experiments with over nine implementations of concurrent sets,
including Intel's TBB library, show that our linearizability checker is one
order of magnitude faster and/or more space efficient than the state-of-the-art
algorithm.Comment: 15 pages, 2 figure
Causal Consistent Databases
Many consistency criteria have been considered in databases and the causal consistency is one of them. The causal consistency model has gained much attention in recent years because it provides ordering of relative operations. The causal consistency requires that all writes, which are potentially causally related, must be seen in the same order by all processes. The causal consistency is a weaker criteria than the sequential consistency, because there exists an execution, which is causally consistent but not sequentially consistent, however all executions satisfying the sequential consistency are also causally consistent. Furthermore, the causal consistency supports non-blocking operations; i.e. processes may complete read or write operations without waiting for global computation. Therefore, the causal consistency overcomes the primary limit of stronger criteria: communication latency. Additionally, several application semantics are precisely captured by the causal consistency, e.g. collaborative tools. In this paper, we review the state-of-the-art of causal consistent databases, discuss the features, functionalities and applications of the causal consistency model, and systematically compare it with other consistency models. We also discuss the implementation of causal consistency databases and identify limitations of the causal consistency model
Safety Verification of Parameterized Systems under Release-Acquire
We study the safety verification problem for parameterized systems under the
release-acquire (RA) semantics. It has been shown that the problem is
intractable for systems with unlimited access to atomic compare-and-swap (CAS)
instructions. We show that, from a verification perspective where approximate
results help, this is overly pessimistic. We study parameterized systems
consisting of an unbounded number of environment threads executing identical
but CAS-free programs and a fixed number of distinguished threads that are
unrestricted.
Our first contribution is a new semantics that considerably simplifies RA but
is still equivalent for the above systems as far as safety verification is
concerned. We apply this (general) result to two subclasses of our model. We
show that safety verification is only \pspace-complete for the bounded model
checking problem where the distinguished threads are loop-free. Interestingly,
we can still afford the unbounded environment. We show that the complexity
jumps to \nexp-complete for thread-modular verification where an unrestricted
distinguished `ego' thread interacts with an environment of CAS-free threads
plus loop-free distinguished threads (as in the earlier setting). Besides the
usefulness for verification, the results are strong in that they delineate the
tractability border for an established semantics
Model checking concurrent and real-time systems : the PAT approach
Ph.DDOCTOR OF PHILOSOPH