”To Store or Not To Store” Reloaded: Reclaiming Memory on Demand

Hammer, Moritz; Weber, M.

doi:10.1007/978-3-540-70952-7_4

Cited by 24 publications

(24 citation statements)

References 14 publications

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“…The virtual machine is used as state-space generation component in an adaptive external-memory model checking tool [10].…”

Section: An External-memory Model Checkermentioning

confidence: 99%

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An embeddable virtual machine for state space generation

Weber

2010

Int J Softw Tools Technol Transfer

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Abstract. The semantics of modelling languages are not always specified in a precise and formal way, and their rather complex underlying models make it a non-trivial exercise to reuse them in newly developed tools. We report on experiments with a virtual machine-based approach for state space generation. The virtual machine's (VM) byte-code language is straightforwardly implementable, facilitates reuse and makes it an adequate target for translation of higher-level languages like the SPIN model checker's Promela, or even C. As added value, it provides efficiently executable operational semantics for modelling languages. Several tools have been built on top of the VM implementation we developed, to evaluate the benefits of the proposed approach.

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“…The virtual machine is used as state-space generation component in an adaptive external-memory model checking tool [10].…”

Section: An External-memory Model Checkermentioning

confidence: 99%

“…For the first two models an arbitrary limit of 2.5 GB RAM was set, whereas the other models were given 16 GB RAM. A full account of the experiments and the models is given in [10]. …”

Section: A Benchmarksmentioning

confidence: 99%

An embeddable virtual machine for state space generation

Weber

2010

Int J Softw Tools Technol Transfer

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“…There are also techniques that purely focus on increasing the amount of available computational power. These are, for example, techniques to fight memory limits with efficient utilisation of an external I/O device [2,19,24,28,32], or techniques that introduce cluster-based algorithms to employ aggregate power of network-interconnected computers.Cluster-based algorithms perform their computation simultaneously on a number of workstations that are allowed to communicate and synchronise themselves by means of message passing. Cluster-based algorithms can thus be characterised as parallel algorithms performing in a distributed memory environment.…”

mentioning

confidence: 99%

Distributed Verification: Exploring the Power of Raw Computing Power

Brim

2007

Formal Methods: Applications and Technology

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Brute-Force in Distribute VerificationWith the increase in complexity of computer systems, it becomes more important to develop formal methods for ensuring their quality and reliability. Various techniques for automated and semi-automated analysis and verification have been successfully applied to real-life computer systems. However, these techniques are computationally hard and memory intensive in general and their applicability to extremely large systems is limited. The major hampering factor is the state space explosion problem due to which large industrial models cannot be efficiently handled by a single state-of-the-art computer.Much attention has been focused on the development of approaches to battle the state space explosion problem. Many techniques, such as abstraction, state compression, state space reduction, symbolic state representation, etc., are used to reduce the size of the problem to be handled allowing thus a single computer to process larger systems. There are also techniques that purely focus on increasing the amount of available computational power. These are, for example, techniques to fight memory limits with efficient utilisation of an external I/O device [2,19,24,28,32], or techniques that introduce cluster-based algorithms to employ aggregate power of network-interconnected computers.Cluster-based algorithms perform their computation simultaneously on a number of workstations that are allowed to communicate and synchronise themselves by means of message passing. Cluster-based algorithms can thus be characterised as parallel algorithms performing in a distributed memory environment. The algorithms prove their usefulness in verification of large-scale systems. They have been successfully applied to symbolic model checking [22,23], analysis of stochastic [25] and timed [6] systems, equivalence checking [8] and other related problems [7,9,21].The idea of parallel verification appeared already in the very early years of the formal verification era. However, inaccessibility of cheap parallel computers together with negative theoretical complexity results excluded this approach from the main stream in formal verification. The situation changed dramatically during the past several years. Computer progress over the past two decades has measured several orders of magnitude with respect to various physical parameters such as computing power, memory size at all hierarchy levels from caches to disk, power consumption, physical size and cost.

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“…Hammer and Weber [21] implemented an external memory search that takes a cue from the partial storage algorithms. The Hammer algorithm uses a function to guess which states are less likely to be duplicated and swaps them to external memory.…”

Section: Locality In Ram Cachementioning

confidence: 99%

Layered Duplicate Detection in External-Memory Model Checking

Lamborn

Hansen

Model Checking Software

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Abstract. This paper presents a disk-based explicit state model checking algorithm that uses an approach called layered duplicate detection. In this approach, states encountered during a breadth-first traversal of the graph of the transition system are stored in memory according to the layer of the graph in which they are first encountered. With this layered organization of memory, transition locality is exploited by checking only the most recent layers for duplicates. In RAM, exploiting transition locality in this way saves time. In external memory, it saves space. In addition, a layered structure allows an easy method of counterexample reconstruction in disk-based model checking. We prove a worst-case linear bound on the redundant work performed by our approach. Experimental results indicate that average case redundant work is much better than the worst-case. The implemented model checker has been used to verify a transition system that required more than 275 GBs of disk storage.

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”To Store or Not To Store” Reloaded: Reclaiming Memory on Demand

Cited by 24 publications

References 14 publications

An embeddable virtual machine for state space generation

An embeddable virtual machine for state space generation

Distributed Verification: Exploring the Power of Raw Computing Power

Layered Duplicate Detection in External-Memory Model Checking

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