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Automated verification of refinement laws
Demonic refinement algebras are variants of Kleene algebras. Introduced by von Wright as a light-weight variant of the refinement calculus, their intended semantics are positively disjunctive predicate transformers, and their calculus is entirely within first-order equational logic. So, for the first time, off-the-shelf automated theorem proving (ATP) becomes available for refinement proofs. We used ATP to verify a toolkit of basic refinement laws. Based on this toolkit, we then verified two classical complex refinement laws for action systems by ATP: a data refinement law and Back's atomicity refinement law. We also present a refinement law for infinite loops that has been discovered through automated analysis. Our proof experiments not only demonstrate that refinement can effectively be automated, they also compare eleven different ATP systems and suggest that program verification with variants of Kleene algebras yields interesting theorem proving benchmarks. Finally, we apply hypothesis learning techniques that seem indispensable for automating more complex proofs
Simplifying proofs of linearisability using layers of abstraction
Linearisability has become the standard correctness criterion for concurrent
data structures, ensuring that every history of invocations and responses of
concurrent operations has a matching sequential history. Existing proofs of
linearisability require one to identify so-called linearisation points within
the operations under consideration, which are atomic statements whose execution
causes the effect of an operation to be felt. However, identification of
linearisation points is a non-trivial task, requiring a high degree of
expertise. For sophisticated algorithms such as Heller et al's lazy set, it
even is possible for an operation to be linearised by the concurrent execution
of a statement outside the operation being verified. This paper proposes an
alternative method for verifying linearisability that does not require
identification of linearisation points. Instead, using an interval-based logic,
we show that every behaviour of each concrete operation over any interval is a
possible behaviour of a corresponding abstraction that executes with
coarse-grained atomicity. This approach is applied to Heller et al's lazy set
to show that verification of linearisability is possible without having to
consider linearisation points within the program code
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
Reasoning algebraically about refinement on TSO architectures
The Total Store Order memory model is widely implemented by modern multicore architectures such as x86, where local buffers are used for optimisation, allowing limited forms of instruction reordering. The presence of buffers and hardware-controlled buffer flushes increases the level of non-determinism from the level specified by a program, complicating the already difficult task of concurrent programming. This paper presents a new notion of refinement for weak memory models, based on the observation that pending writes to a process' local variables may be treated as if the effect of the update has already occurred in shared memory. We develop an interval-based model with algebraic rules for various programming constructs. In this framework, several decomposition rules for our new notion of refinement are developed. We apply our approach to verify the spinlock algorithm from the literature
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