Unfolding-based Partial Order Reduction

Partial order reduction (POR) and net unfoldings are two alternative methods to tackle state-space explosion caused by concurrency. In this paper, we propose the combination of both approaches in an effort to combine their strengths. We first define, for an abstract execution model, unfolding semantics parameterized over an arbitrary independence relation. Based on it, our main contribution is a novel stateless POR algorithm that explores at most one execution per Mazurkiewicz trace, and in general, can explore exponentially fewer, thus achieving a form of super-optimality. Furthermore, our unfolding-based POR copes with non-terminating executions and incorporates state-caching. Over benchmarks with busy-waits, among others, our experiments show a dramatic reduction in the number of executions when compared to a state-of-the-art DPOR.Comment: Long version of a paper with the same title appeared on the proceedings of CONCUR 201

Partial Order Reduction with Compositional Verification

This thesis expands the usage of partial order reduction methods in reducing the state space of large models in model checking. The work done can be divided into two parts. In the first part we introduce two new ample conditions that utilise strongly connected components in place of two existing ample conditions that use cycles. We use these new conditions to optimise existing partial order reduction verifiers and extend them to verify nonblocking properties. We also introduce two selection strategies for choosing ample event sets and an improved ample algorithm in order to improve the efficiency of ample set computation, and investigate how the various combinations of these suggested algorithmic improvements effect several models of varying size. The second part of the thesis introduces the concept of using partial order reduction techniques in combination with compositional verification techniques. We introduce a modified version of the silent continuation rule that makes use of the independence relationship from partial order reduction methods and include algorithms by which they may be implemented in a model verifier. All of the original concepts developed in this thesis are also proven correct

A partial order reduction algorithm without the Proviso

Journal ArticleThis paper presents a partial order reduction algorithm, called Two phase, that preserves stutter free LTL properties. Two phase dramatically reduces the number of states visited compared to previous partial order reduction algorithms on most practical protocols. The reason can be traced to a step of the previous algorithms, called the proviso step, that specifies a condition on how a state that closes a loop is expanded. Two phase can be easily combined with an on-the-fly model-checking algorithm to reduce the memory requirements further. Furthermore a simple but powerful selective-caching scheme can also be added to Two phase. Two phase has been implemented in a model-checker called PV (Protocol Verifier) and is in routine use on large problems

A Pragmatic Approach to Stateful Partial Order Reduction

Partial order reduction (POR) is a classic technique for dealing with the state explosion problem in model checking of concurrent programs. Theoretical optimality, i.e., avoiding enumerating equivalent interleavings, does not necessarily guarantee optimal overall performance of the model checking algorithm. The computational overhead required to guarantee optimality may by far cancel out any benefits that an algorithm may have from exploring a smaller state space of interleavings. With a focus on overall performance, we propose new algorithms for stateful POR based on the recently proposed source sets, which are less precise but more efficient than the state of the art in practice. We evaluate efficiency using an implementation that extends Java Pathfinder in the context of verifying concurrent data structures

An improvement in partial order reduction using behavioral analysis

pre-printEfficacy of partial order reduction in reducing state space relies on adequate extraction of the independence relation among possible behaviors. However, traditional approaches by statically analyzing system model structures are often not able to reveal enough independence for reduction. To address such a problem, this paper presents a behavioral analysis approach that uses a compositional reachability analysis method to generate the over-approximate local state spaces for all modules in a system where a much more precise independence relation can be extracted for partial order reduction. Compared to the static analysis approaches, significantly higher reduction on complexity can be seen in a number of non-trivial examples, and as a consequence, dramatically less time and memory are required to finish these examples

Compositional Correctness and Completeness for Symbolic Partial Order Reduction

Partial Order Reduction (POR) and Symbolic Execution (SE) are two fundamental abstraction techniques in program analysis. SE is particularly useful as a state abstraction technique for sequential programs, while POR addresses equivalent interleavings in the execution of concurrent programs. Recently, several promising connections between these two approaches have been investigated, which result in symbolic partial order reduction: partial order reduction of symbolically executed programs. In this work, we provide compositional notions of completeness and correctness for symbolic partial order reduction. We formalize completeness and correctness for (1) abstraction over program states and (2) trace equivalence, such that the abstraction gives rise to a complete and correct SE, the trace equivalence gives rise to a complete and correct POR, and their combination results in complete and correct symbolic partial order reduction. We develop our results for a core parallel imperative programming language and mechanize the proofs in Coq